1
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Jin S, Dickens BL, Lim JT, Cook AR. EpiMix: A novel method to estimate effective reproduction number. Infect Dis Model 2023; 8:704-716. [PMID: 37416322 PMCID: PMC10320401 DOI: 10.1016/j.idm.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 06/14/2023] [Accepted: 06/14/2023] [Indexed: 07/08/2023] Open
Abstract
Transmission potential of a pathogen, often quantified by the time-varying reproduction number Rt, provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for Rt estimation, wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework. Using Integrated Nested Laplace Approximation, EpiMix is able to efficiently generate reliable, deterministic Rt estimates. In the simulations and case studies performed, we further demonstrated the method's robustness in low-incidence scenarios, together with other merits, including its flexibility in selecting variables and tolerance of varying reporting rates. All these make EpiMix a potentially useful tool for real-time Rt estimation provided that the serial interval distribution, time series of case counts and external influencing factors are available.
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Affiliation(s)
- Shihui Jin
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Borame Lee Dickens
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Jue Tao Lim
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Alex R. Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Department of Statistics and Data Science, National University of Singapore, Singapore
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2
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Olumekor M, Stojić A, Kehler T, Polo F. The Impact of COVID-19 on the Quality of Life and Happiness of Care Home Residents in Croatia: A Cross-Sectional Study. Behav Sci (Basel) 2022; 12:463. [PMID: 36421759 PMCID: PMC9687193 DOI: 10.3390/bs12110463] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/14/2022] [Accepted: 11/15/2022] [Indexed: 09/08/2024] Open
Abstract
Care/nursing homes globally have been severely affected by the COVID-19 pandemic and have disproportionately experienced a high rate of mortality which led to the introduction of strict isolation policies. However, while there are studies on the mortality, epidemiology, staffing challenges, and mismanagement in long-term care homes as a result of COVID-19, there appears to be a paucity of information regarding the Quality of Life (QoL), happiness, and associated well-being of the elderly residents of these homes. Therefore, we examined if COVID-19 affected the happiness level, QoL, and financial condition of long-term care home residents in Croatia. To achieve this, a survey of 308 participants in eight long term care homes was conducted. Descriptive analysis was performed to describe the mean of all responses and the Bayesian Integrated Nested Laplace Approximation (INLA) was used to provide a detailed quantitative analysis of the results. We found that the QoL and happiness of residents remained relatively stable during the COVID-19 pandemic. However, the income level, financial outlook, marital status, and vaccination positivity influenced the QoL and happiness of care home residents to a considerable degree. We recommend that policy makers pay attention to these underlying factors.
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Affiliation(s)
- Michael Olumekor
- Graduate School of Economics and Management, Ural Federal University, 620014 Yekaterinburg, Russia
| | - Andrea Stojić
- Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia
| | - Tatjana Kehler
- Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia
| | - Francesco Polo
- Cultural Centre Humanitas in Conegliano, 31015 Treviso, Italy
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3
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Wijewardhana UA, Apputhurai P, Jayawardana M, Meyer D. Effectiveness of the conservation areas on the Mornington Peninsula for the common resident shorebird species using citizen science data. PLoS One 2022; 17:e0267203. [PMID: 35507597 PMCID: PMC9067883 DOI: 10.1371/journal.pone.0267203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/04/2022] [Indexed: 11/30/2022] Open
Abstract
Conservation areas are critical for biodiversity conservation, but few citizen science studies have evaluated their efficiency. In the absence of thorough survey data, this study assessed which species benefit most from conservation areas using citizen science bird counts extracted from the Atlas of Living Australia. This was accomplished by fitting temporal models using citizen science data taken from ALA for the years 2010-2019 using the INLA approach. The trends for six resident shorebird species were compared to those for the Australian Pied Oystercatcher, with the Black-fronted Dotterel, Red-capped Dotterel, and Red-kneed Dotterel exhibiting significantly steeper increasing trends. For the Black-fronted Dotterel, Masked Lapwing, and Red-kneed Dotterel, steeper rising trends were recorded in conservation areas than in other locations. The Dotterel species' conservation status is extremely favourable. This study demonstrates that, with some limits, statistical models can be used to track the persistence of resident shorebirds and to investigate the factors affecting these data.
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Affiliation(s)
- Udani Abhisheka Wijewardhana
- Department of Health Science and Biostatistics, School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Pragalathan Apputhurai
- Department of Health Science and Biostatistics, School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Madawa Jayawardana
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria, Australia
| | - Denny Meyer
- Department of Health Science and Biostatistics, School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
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4
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Susak H, Serra-Saurina L, Demidov G, Rabionet R, Domènech L, Bosio M, Muyas F, Estivill X, Escaramís G, Ossowski S. Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation. PLoS Comput Biol 2021; 17:e1007784. [PMID: 33606672 PMCID: PMC7928502 DOI: 10.1371/journal.pcbi.1007784] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 03/03/2021] [Accepted: 01/04/2021] [Indexed: 12/02/2022] Open
Abstract
Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the 'Rare Variant Genome Wide Association Study' (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.
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Affiliation(s)
- Hana Susak
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Laura Serra-Saurina
- Biomedical Research Networking Centre consortium of Public Health and Epidemiology (CIBERESP), Madrid, Spain
- Center for research in occupational Health (CiSAL), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Research Group on Statistics, Econometrics and Health (GRECS), Universitat de Girona (UdG), Girona, Spain
| | - German Demidov
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Raquel Rabionet
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, IBUB, Universitat de Barcelona; CIBERER, IRSJD, Barcelona, Spain
| | - Laura Domènech
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Biomedical Research Networking Centre consortium of Public Health and Epidemiology (CIBERESP), Madrid, Spain
| | - Mattia Bosio
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Francesc Muyas
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
| | - Xavier Estivill
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Women’s Health Dexeus, Barcelona, Spain
| | - Geòrgia Escaramís
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Biomedical Research Networking Centre consortium of Public Health and Epidemiology (CIBERESP), Madrid, Spain
- Departament de Biomedicina, Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona, Spain
| | - Stephan Ossowski
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany
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5
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Nikoloulopoulos AK. An extended trivariate vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable outcomes. Int J Biostat 2020; 16:/j/ijb.ahead-of-print/ijb-2019-0107/ijb-2019-0107.xml. [PMID: 32772003 DOI: 10.1515/ijb-2019-0107] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 04/06/2020] [Indexed: 11/15/2022]
Abstract
A recent paper proposed an extended trivariate generalized linear mixed model (TGLMM) for synthesis of diagnostic test accuracy studies in the presence of non-evaluable index test results. Inspired by the aforementioned model we propose an extended trivariate vine copula mixed model that includes the TGLMM as special case, but can also operate on the original scale of sensitivity, specificity, and disease prevalence. The performance of the proposed vine copula mixed model is examined by extensive simulation studies in comparison with the TGLMM. Simulation studies showed that the TGLMM leads to biased meta-analytic estimates of sensitivity, specificity, and prevalence when the univariate random effects are misspecified. The vine copula mixed model gives nearly unbiased estimates of test accuracy indices and disease prevalence. Our general methodology is illustrated by meta-analysing coronary CT angiography studies.
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6
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Negeri ZF, Beyene J. Robust bivariate random-effects model for accommodating outlying and influential studies in meta-analysis of diagnostic test accuracy studies. Stat Methods Med Res 2020; 29:3308-3325. [PMID: 32469266 DOI: 10.1177/0962280220925840] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Due to the inevitable inter-study correlation between test sensitivity (Se) and test specificity (Sp), mostly because of threshold variability, hierarchical or bivariate random-effects models are widely used to perform a meta-analysis of diagnostic test accuracy studies. Conventionally, these models assume that the random-effects follow the bivariate normal distribution. However, the inference made using the well-established bivariate random-effects models, when outlying and influential studies are present, may lead to misleading conclusions, since outlying or influential studies can extremely influence parameter estimates due to their disproportional weight. Therefore, we developed a new robust bivariate random-effects model that accommodates outlying and influential observations and gives robust statistical inference by down-weighting the effect of outlying and influential studies. The marginal model and the Monte Carlo expectation-maximization algorithm for our proposed model have been derived. A simulation study has been carried out to validate the proposed method and compare it against the standard methods. Regardless of the parameters varied in our simulations, the proposed model produced robust point estimates of Se and Sp compared to the standard models. Moreover, our proposed model resulted in precise estimates as it yielded the narrowest confidence intervals. The proposed model also generated a similar point and interval estimates of Se and Sp as the standard models when there are no outlying and influential studies. Two published meta-analyses have also been used to illustrate the methods.
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Affiliation(s)
- Zelalem F Negeri
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada
| | - Joseph Beyene
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada.,Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
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7
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Nikoloulopoulos AK. A multinomial quadrivariate D-vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable subjects. Stat Methods Med Res 2020; 29:2988-3005. [PMID: 32323626 PMCID: PMC7682507 DOI: 10.1177/0962280220913898] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Diagnostic test accuracy studies observe the result of a gold standard procedure that defines the presence or absence of a disease and the result of a diagnostic test. They typically report the number of true positives, false positives, true negatives and false negatives. However, diagnostic test outcomes can also be either non-evaluable positives or non-evaluable negatives. We propose a novel model for the meta-analysis of diagnostic studies in the presence of non-evaluable outcomes, which assumes independent multinomial distributions for the true and non-evaluable positives, and, the true and non-evaluable negatives, conditional on the latent sensitivity, specificity, probability of non-evaluable positives and probability of non-evaluable negatives in each study. For the random effects distribution of the latent proportions, we employ a drawable vine copula that can successively model the dependence in the joint tails. Our methodology is demonstrated with an extensive simulation study and applied to data from diagnostic accuracy studies of coronary computed tomography angiography for the detection of coronary artery disease. The comparison of our method with the existing approaches yields findings in the real data application that change the current conclusions.
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8
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Negeri ZF, Beyene J. Skew-normal random-effects model for meta-analysis of diagnostic test accuracy (DTA) studies. Biom J 2020; 62:1223-1244. [PMID: 32022315 DOI: 10.1002/bimj.201900184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 12/11/2019] [Accepted: 12/11/2019] [Indexed: 11/10/2022]
Abstract
Hierarchical models are recommended for meta-analyzing diagnostic test accuracy (DTA) studies. The bivariate random-effects model is currently widely used to synthesize a pair of test sensitivity and specificity using logit transformation across studies. This model assumes a bivariate normal distribution for the random-effects. However, this assumption is restrictive and can be violated. When the assumption fails, inferences could be misleading. In this paper, we extended the current bivariate random-effects model by assuming a flexible bivariate skew-normal distribution for the random-effects in order to robustly model logit sensitivities and logit specificities. The marginal distribution of the proposed model is analytically derived so that parameter estimation can be performed using standard likelihood methods. The method of weighted-average is adopted to estimate the overall logit-transformed sensitivity and specificity. An extensive simulation study is carried out to investigate the performance of the proposed model compared to other standard models. Overall, the proposed model performs better in terms of confidence interval width of the average logit-transformed sensitivity and specificity compared to the standard bivariate linear mixed model and bivariate generalized linear mixed model. Simulations have also shown that the proposed model performed better than the well-established bivariate linear mixed model in terms of bias and comparable with regards to the root mean squared error (RMSE) of the between-study (co)variances. The proposed method is also illustrated using a published meta-analysis data.
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Affiliation(s)
- Zelalem F Negeri
- Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada
| | - Joseph Beyene
- Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada.,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
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9
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Diagnostic Performance of CT for Occult Proximal Femoral Fractures: A Systematic Review and Meta-Analysis. AJR Am J Roentgenol 2019; 213:1324-1330. [DOI: 10.2214/ajr.19.21510] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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10
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Veličković VM, Rochau U, Conrads-Frank A, Kee F, Blankenberg S, Siebert U. Systematic assessment of decision-analytic models evaluating diagnostic tests for acute myocardial infarction based on cardiac troponin assays. Expert Rev Pharmacoecon Outcomes Res 2018; 18:619-640. [DOI: 10.1080/14737167.2018.1512857] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Vladica M. Veličković
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
- Faculty of Medicine, University of Niš, Nis, Serbia
| | - Ursula Rochau
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
- Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
| | - Annette Conrads-Frank
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Frank Kee
- UKCRC Centre of Excellence for Public Health Research, Queens University Belfast, Belfast, United Kingdom
| | - Stefan Blankenberg
- Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), Hamburg, Germany
| | - Uwe Siebert
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
- Area 4 Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
- Center for Health Decision Science, Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA
- Program on Cardiovascular Research, Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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11
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Negeri ZF, Shaikh M, Beyene J. Bivariate random-effects meta-analysis models for diagnostic test accuracy studies using arcsine-based transformations. Biom J 2018; 60:827-844. [PMID: 29748967 DOI: 10.1002/bimj.201700101] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2017] [Revised: 01/30/2018] [Accepted: 02/26/2018] [Indexed: 11/11/2022]
Abstract
Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets.
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Affiliation(s)
- Zelalem F Negeri
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada, L8S 4K1
| | - Mateen Shaikh
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada, L8S 4K1
| | - Joseph Beyene
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada, L8S 4K1.,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada, L8S 4K1
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12
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Hoyer A, Kuss O. Meta-analysis for the comparison of two diagnostic tests-A new approach based on copulas. Stat Med 2018; 37:739-748. [PMID: 29193212 DOI: 10.1002/sim.7556] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Revised: 08/09/2017] [Accepted: 10/15/2017] [Indexed: 11/08/2022]
Abstract
Meta-analysis of diagnostic studies is still field of ongoing biometrical research. Especially, clinical researchers call for methods that allow for a comparison of different diagnostic tests to a common gold standard. Focussing on two diagnostic tests, the main parameters of interest are differences of sensitivities and specificities (with their corresponding confidence intervals) between the two diagnostic tests while accounting for the various associations across the two tests and the single studies. Similar to our previous work using generalized linear mixed models to this task, we propose a model with a quadrivariate response consisting of the two sensitivities and the two specificities of both tests. This new approach uses the ideas of copula modelling, and especially a quadrivariate Gaussian copula and a quadrivariate vine copula, which is built from bivariate Plackett copulas. The different copulas are compared in a simulation study and illustrated by the application of population-based screening for type 2 diabetes.
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Affiliation(s)
- Annika Hoyer
- German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Institute for Biometrics and Epidemiology, 40225 Düsseldorf, Germany
| | - Oliver Kuss
- German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Institute for Biometrics and Epidemiology, 40225 Düsseldorf, Germany
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13
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Sawaguchi T. [Approach to the Development of Mind and Persona]. Nihon Eiseigaku Zasshi 2018; 73:67-74. [PMID: 29386450 DOI: 10.1265/jjh.73.67] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVES To access medical specialists by health specialists working in the regional health field, the possibility of utilizing the voice approach for dissociative identity disorder (DID) patients as a health assessment for medical access (HAMA) was investigated. The first step is to investigate whether the plural personae in a single DID patient can be discriminated by voice analysis. METHODS Voices of DID patients including these with different personae were extracted from YouTube and were analysed using the software PRAAT with basic frequency, oral factors, chin factors and tongue factors. In addition, RAKUGO story teller voices made artificially and dramatically were analysed in the same manner. Quantitive and qualitative analysis method were carried out and nested logistic regression and a nested generalized linear model was developed. RESULTS The voice from different personae in one DID patient could be visually and easily distinquished using basic frequency curve, cluster analysis and factor analysis. In the canonical analysis, only Roy's maximum root was <0.01. In the nested generalized linear model, the model using a standard deviation (SD) indicator fit best and some other possibilities are shown here. CONCLUSIONS In DID patients, the short transition time among plural personae could guide to the risky situation such as suicide. So if the voice approach can show the time threshold of changes between the different personae, it would be useful as an Access Assessment in the form of a simple HAMA.
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Affiliation(s)
- Toshiko Sawaguchi
- National Institute of Public Health, Ministry of Health, Labor, and Welfare.,Department of Legal Medicine, Showa University School of Medicine
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14
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Günhan BK, Friede T, Held L. A design-by-treatment interaction model for network meta-analysis and meta-regression with integrated nested Laplace approximations. Res Synth Methods 2018; 9:179-194. [PMID: 29193801 PMCID: PMC6001639 DOI: 10.1002/jrsm.1285] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 11/05/2017] [Accepted: 11/11/2017] [Indexed: 11/05/2022]
Abstract
Network meta-analysis (NMA) is gaining popularity for comparing multiple treatments in a single analysis. Generalized linear mixed models provide a unifying framework for NMA, allow us to analyze datasets with dichotomous, continuous or count endpoints, and take into account multiarm trials, potential heterogeneity between trials and network inconsistency. To perform inference within such NMA models, the use of Bayesian methods is often advocated. The standard inference tool is Markov chain Monte Carlo (MCMC), which is computationally expensive and requires convergence diagnostics. A deterministic approach to do fully Bayesian inference for latent Gaussian models can be achieved by integrated nested Laplace approximations (INLA), which is a fast and accurate alternative to MCMC. We show how NMA models fit in the class of latent Gaussian models and how NMA models are implemented using INLA and demonstrate that the estimates obtained by INLA are in close agreement with the ones obtained by MCMC. Specifically, we emphasize the design-by-treatment interaction model with random inconsistency parameters (also known as the Jackson model). Also, we have proposed a network meta-regression model, which is constructed by incorporating trial-level covariates to the Jackson model to explain possible sources of heterogeneity and/or inconsistency in the network. A publicly available R package, nmaINLA, is developed to automate the INLA implementation of NMA models, which are considered in this paper. Three applications illustrate the use of INLA for a NMA.
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Affiliation(s)
- Burak Kürsad Günhan
- Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
| | - Tim Friede
- Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
| | - Leonhard Held
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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15
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Belleville S, Fouquet C, Hudon C, Zomahoun HTV, Croteau J. Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis. Neuropsychol Rev 2017; 27:328-353. [PMID: 29019061 PMCID: PMC5754432 DOI: 10.1007/s11065-017-9361-5] [Citation(s) in RCA: 173] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 09/04/2017] [Indexed: 11/28/2022]
Abstract
This study aimed to determine the extent to which cognitive measures can predict progression from mild cognitive impairment (MCI) to Alzheimer’s type dementia (AD), assess the predictive accuracy of different cognitive domain categories, and determine whether accuracy varies as a function of age and length of follow-up. We systematically reviewed and meta-analyzed data from longitudinal studies reporting sensitivity and specificity values for neuropsychological tests to identify individuals with MCI who will develop AD. We searched articles in Medline, Cochrane, EMBASE, PsycINFO, and the Web of Science. Methodological quality was assessed using the STARDem and QUADAS standards. Twenty-eight studies met the eligibility criteria (2365 participants) and reported predictive values from 61 neuropsychological tests with a 31-month mean follow-up. Values were pooled to provide combined accuracy for 14 cognitive domains. Many domains showed very good predictive accuracy with high sensitivity and specificity values (≥ 0.7). Verbal memory measures and many language tests yielded very high predictive accuracy. Other domains (e.g., executive functions, visual memory) showed better specificity than sensitivity. Predictive accuracy was highest when combining memory measures with a small set of other domains or when relying on broad cognitive batteries. Cognitive tests are excellent at predicting MCI individuals who will progress to dementia and should be a critical component of any toolkit intended to identify AD at the pre-dementia stage. Some tasks are remarkable as early indicators, whereas others might be used to suggest imminent progression.
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Affiliation(s)
- Sylvie Belleville
- Research Center of the Institut Universitaire de Gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, Québec, H3W 1W5, Canada. .,Université de Montréal, CP 6128 Succ. Centre Ville, Montréal, Québec, H3C-1J7, Canada.
| | - Céline Fouquet
- Research Center of the Institut Universitaire de Gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, Québec, H3W 1W5, Canada
| | - Carol Hudon
- Université Laval, Pavillon Félix-Antoine-Savard, 2325, rue des Bibliothèques, Local 1546, Québec, Québec, G1V 0A6, Canada.,CERVO Brain Research Center, 2601, de la Canardiere, Québec, Québec, G1J 2G3, Canada
| | - Hervé Tchala Vignon Zomahoun
- Health and Social Services Systems, Knowledge Translation and Implementation component of the Quebec SPOR-SUPPORT Unit, Université Laval, Québec, Québec, G1L 2E8, Canada.,Population Health and Practice-Changing Research Group, Research Centre of CHU de Québec- Université Laval, Québec, Québec, G1L 2E8, Canada
| | - Jordie Croteau
- Health and Social Services Systems, Knowledge Translation and Implementation component of the Quebec SPOR-SUPPORT Unit, Université Laval, Québec, Québec, G1L 2E8, Canada.,Population Health and Practice-Changing Research Group, Research Centre of CHU de Québec- Université Laval, Québec, Québec, G1L 2E8, Canada
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16
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Guo J, Riebler A, Rue H. Bayesian bivariate meta-analysis of diagnostic test studies with interpretable priors. Stat Med 2017; 36:3039-3058. [PMID: 28474394 DOI: 10.1002/sim.7313] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Revised: 03/27/2017] [Accepted: 03/27/2017] [Indexed: 11/11/2022]
Abstract
In a bivariate meta-analysis, the number of diagnostic studies involved is often very low so that frequentist methods may result in problems. Using Bayesian inference is particularly attractive as informative priors that add a small amount of information can stabilise the analysis without overwhelming the data. However, Bayesian analysis is often computationally demanding and the selection of the prior for the covariance matrix of the bivariate structure is crucial with little data. The integrated nested Laplace approximations method provides an efficient solution to the computational issues by avoiding any sampling, but the important question of priors remain. We explore the penalised complexity (PC) prior framework for specifying informative priors for the variance parameters and the correlation parameter. PC priors facilitate model interpretation and hyperparameter specification as expert knowledge can be incorporated intuitively. We conduct a simulation study to compare the properties and behaviour of differently defined PC priors to currently used priors in the field. The simulation study shows that the PC prior seems beneficial for the variance parameters. The use of PC priors for the correlation parameter results in more precise estimates when specified in a sensible neighbourhood around the truth. To investigate the usage of PC priors in practice, we reanalyse a meta-analysis using the telomerase marker for the diagnosis of bladder cancer and compare the results with those obtained by other commonly used modelling approaches. Copyright © 2017 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jingyi Guo
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, PO 7491, Norway
| | - Andrea Riebler
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, PO 7491, Norway
| | - Håvard Rue
- Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, PO 7491, Norway
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17
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Guolo A. A double SIMEX approach for bivariate random-effects meta-analysis of diagnostic accuracy studies. BMC Med Res Methodol 2017; 17:6. [PMID: 28077079 PMCID: PMC5225626 DOI: 10.1186/s12874-016-0284-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 12/22/2016] [Indexed: 11/15/2022] Open
Abstract
Background Bivariate random-effects models represent a widely accepted and recommended approach for meta-analysis of test accuracy studies. Standard likelihood methods routinely used for inference are prone to several drawbacks. Small sample size can give rise to unreliable inferential conclusions and convergence issues make the approach unappealing. This paper suggests a different methodology to address such difficulties. Methods A SIMEX methodology is proposed. The method is a simulation-based technique originally developed as a correction strategy within the measurement error literature. It suits the meta-analysis framework as the diagnostic accuracy measures provided by each study are prone to measurement error. SIMEX can be straightforwardly adapted to cover different measurement error structures and to deal with covariates. The effortless implementation with standard software is an interesting feature of the method. Results Extensive simulation studies highlight the improvement provided by SIMEX over likelihood approach in terms of empirical coverage probabilities of confidence intervals under different scenarios, independently of the sample size and the values of the correlation between sensitivity and specificity. A remarkable amelioration is obtained in case of deviations from the normality assumption for the random-effects distribution. From a computational point of view, the application of SIMEX is shown to be neither involved nor subject to the convergence issues affecting likelihood-based alternatives. Application of the method to a diagnostic review of the performance of transesophageal echocardiography for assessing ascending aorta atherosclerosis enables overcoming limitations of the likelihood procedure. Conclusions The SIMEX methodology represents an interesting alternative to likelihood-based procedures for inference in meta-analysis of diagnostic accuracy studies. The approach can provide more accurate inferential conclusions, while avoiding convergence failure and numerical instabilities. The application of the method in the R programming language is possible through the code which is made available and illustrated using the real data example. Electronic supplementary material The online version of this article (doi:10.1186/s12874-016-0284-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Annamaria Guolo
- Department of Statistical Sciences, Via Cesare Battisti 241/243, Padova, Italy.
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18
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Dahabreh IJ, Trikalinos TA, Lau J, Schmid CH. Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference. J Clin Epidemiol 2017; 83:8-17. [PMID: 28063915 DOI: 10.1016/j.jclinepi.2016.12.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2012] [Revised: 10/04/2016] [Accepted: 12/01/2016] [Indexed: 11/16/2022]
Abstract
OBJECTIVES To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). STUDY DESIGN AND SETTING We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. RESULTS We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. CONCLUSION The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters.
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Affiliation(s)
- Issa J Dahabreh
- Center for Evidence Synthesis in Health, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA; Department of Health Services Policy & Practice, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA
| | - Thomas A Trikalinos
- Center for Evidence Synthesis in Health, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA; Department of Health Services Policy & Practice, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA
| | - Joseph Lau
- Center for Evidence Synthesis in Health, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA; Department of Health Services Policy & Practice, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA
| | - Christopher H Schmid
- Center for Evidence Synthesis in Health, School of Public Health, Brown University, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA; Department of Biostatistics, School of Public Health, Brown University, Providence, 121 South Main St, Box G-S121-8, Providence, RI 02912, USA.
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Held L, Muff S. Comment. J Am Stat Assoc 2016. [DOI: 10.1080/01621459.2016.1164705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Leonhard Held
- Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zürich, Switzerland
| | - Stefanie Muff
- Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zürich, Switzerland
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20
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Incorporating High-Dimensional Exposure Modelling into Studies of Air Pollution and Health. STATISTICS IN BIOSCIENCES 2016; 9:559-581. [PMID: 29225714 PMCID: PMC5711999 DOI: 10.1007/s12561-016-9150-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Accepted: 05/20/2016] [Indexed: 11/11/2022]
Abstract
Performing studies on the risks of environmental hazards on human health requires accurate estimates of exposures that might be experienced by the populations at risk. Often there will be missing data and in many epidemiological studies, the locations and times of exposure measurements and health data do not match. To a large extent this will be due to the health and exposure data having arisen from completely different data sources and not as the result of a carefully designed study, leading to problems of both ‘change of support’ and ‘misaligned data’. In such cases, a direct comparison of the exposure and health outcome is often not possible without an underlying model to align the two in the spatial and temporal domains. The Bayesian approach provides the natural framework for such models; however, the large amounts of data that can arise from environmental networks means that inference using Markov Chain Monte Carlo might not be computationally feasible in this setting. Here we adapt the integrated nested Laplace approximation to implement spatio–temporal exposure models. We also propose methods for the integration of large-scale exposure models and health analyses. It is important that any model structure allows the correct propagation of uncertainty from the predictions of the exposure model through to the estimates of risk and associated confidence intervals. The methods are demonstrated using a case study of the levels of black smoke in the UK, measured over several decades, and respiratory mortality.
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21
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A latent process model for forecasting multiple time series in environmental public health surveillance. Stat Med 2016; 35:3085-100. [DOI: 10.1002/sim.6904] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2015] [Revised: 11/26/2015] [Accepted: 01/21/2016] [Indexed: 01/19/2023]
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Bauer C, Wakefield J, Rue H, Self S, Feng Z, Wang Y. Bayesian penalized spline models for the analysis of spatio-temporal count data. Stat Med 2015; 35:1848-65. [PMID: 26530705 DOI: 10.1002/sim.6785] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Revised: 10/02/2015] [Accepted: 10/10/2015] [Indexed: 11/11/2022]
Abstract
In recent years, the availability of infectious disease counts in time and space has increased, and consequently, there has been renewed interest in model formulation for such data. In this paper, we describe a model that was motivated by the need to analyze hand, foot, and mouth disease surveillance data in China. The data are aggregated by geographical areas and by week, with the aims of the analysis being to gain insight into the space-time dynamics and to make short-term predictions, which will aid in the implementation of public health campaigns in those areas with a large predicted disease burden. The model we develop decomposes disease-risk into marginal spatial and temporal components and a space-time interaction piece. The latter is the crucial element, and we use a tensor product spline model with a Markov random field prior on the coefficients of the basis functions. The model can be formulated as a Gaussian Markov random field and so fast computation can be carried out using the integrated nested Laplace approximation approach. A simulation study shows that the model can pick up complex space-time structure and our analysis of hand, foot, and mouth disease data in the central north region of China provides new insights into the dynamics of the disease.
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Affiliation(s)
- Cici Bauer
- Department of Biostatistics, Brown University, Providence, RI, U.S.A
| | - Jon Wakefield
- Department of Statistics, University of Washington, Seattle, WA, U.S.A
| | - Håvard Rue
- Norwegian University of Science and Technology, Trondheim, Norway
| | - Steve Self
- Fred Hutchinson Cancer Research Center, Seattle, WA, U.S.A
| | - Zijian Feng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Wang
- Chinese Center for Disease Control and Prevention, Beijing, China
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23
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Sauter R, Held L. Network meta-analysis with integrated nested Laplace approximations. Biom J 2015; 57:1038-50. [PMID: 26360927 DOI: 10.1002/bimj.201400163] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Revised: 03/23/2015] [Accepted: 05/27/2015] [Indexed: 11/11/2022]
Abstract
Analyzing the collected evidence of a systematic review in form of a network meta-analysis (NMA) enjoys increasing popularity and provides a valuable instrument for decision making. Bayesian inference of NMA models is often propagated, especially if correlated random effects for multiarm trials are included. The standard choice for Bayesian inference is Markov chain Monte Carlo (MCMC) sampling, which is computationally intensive. An alternative to MCMC sampling is the recently suggested approximate Bayesian method of integrated nested Laplace approximations (INLA) that dramatically saves computation time without any substantial loss in accuracy. We show how INLA apply to NMA models for summary level as well as trial-arm level data. Specifically, we outline the modeling of multiarm trials and inference for functional contrasts with INLA. We demonstrate how INLA facilitate the assessment of network inconsistency with node-splitting. Three applications illustrate the use of INLA for a NMA.
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Affiliation(s)
- Rafael Sauter
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, CH-8001 Zürich, Switzerland
| | - Leonhard Held
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, CH-8001 Zürich, Switzerland
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24
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Nikoloulopoulos AK. A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence. Stat Methods Med Res 2015; 26:2270-2286. [PMID: 26265766 DOI: 10.1177/0962280215596769] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.
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25
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Nikoloulopoulos AK. A mixed effect model for bivariate meta-analysis of diagnostic test accuracy studies using a copula representation of the random effects distribution. Stat Med 2015; 34:3842-65. [PMID: 26234584 DOI: 10.1002/sim.6595] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2014] [Revised: 05/01/2015] [Accepted: 07/04/2015] [Indexed: 11/07/2022]
Abstract
Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association between the number of true positives and true negatives, because studies that adopt less stringent criterion for declaring a test positive invoke higher sensitivities and lower specificities. A generalized linear mixed model (GLMM) is currently recommended to synthesize diagnostic test accuracy studies. We propose a copula mixed model for bivariate meta-analysis of diagnostic test accuracy studies. Our general model includes the GLMM as a special case and can also operate on the original scale of sensitivity and specificity. Summary receiver operating characteristic curves are deduced for the proposed model through quantile regression techniques and different characterizations of the bivariate random effects distribution. Our general methodology is demonstrated with an extensive simulation study and illustrated by re-analysing the data of two published meta-analyses. Our study suggests that there can be an improvement on GLMM in fit to data and makes the argument for moving to copula random effects models. Our modelling framework is implemented in the package CopulaREMADA within the open source statistical environment R.
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26
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Zapf A, Hoyer A, Kramer K, Kuss O. Nonparametric meta-analysis for diagnostic accuracy studies. Stat Med 2015; 34:3831-41. [DOI: 10.1002/sim.6583] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Revised: 05/19/2015] [Accepted: 06/18/2015] [Indexed: 11/09/2022]
Affiliation(s)
- Antonia Zapf
- Department of Medical Statistics; University Medical Center Göttingen; Humboldtallee 32 37073 Göttingen Germany
| | - Annika Hoyer
- Institute for Biometry and Epidemiology; German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf; Auf'm Hennekamp 65 40225 Düsseldorf Germany
| | - Katharina Kramer
- Department of Medical Statistics; University Medical Center Göttingen; Humboldtallee 32 37073 Göttingen Germany
| | - Oliver Kuss
- Institute for Biometry and Epidemiology; German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf; Auf'm Hennekamp 65 40225 Düsseldorf Germany
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27
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Takwoingi Y, Guo B, Riley RD, Deeks JJ. Performance of methods for meta-analysis of diagnostic test accuracy with few studies or sparse data. Stat Methods Med Res 2015; 26:1896-1911. [PMID: 26116616 PMCID: PMC5564999 DOI: 10.1177/0962280215592269] [Citation(s) in RCA: 147] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Hierarchical models such as the bivariate and hierarchical summary receiver operating characteristic (HSROC) models are recommended for meta-analysis of test accuracy studies. These models are challenging to fit when there are few studies and/or sparse data (for example zero cells in contingency tables due to studies reporting 100% sensitivity or specificity); the models may not converge, or give unreliable parameter estimates. Using simulation, we investigated the performance of seven hierarchical models incorporating increasing simplifications in scenarios designed to replicate realistic situations for meta-analysis of test accuracy studies. Performance of the models was assessed in terms of estimability (percentage of meta-analyses that successfully converged and percentage where the between study correlation was estimable), bias, mean square error and coverage of the 95% confidence intervals. Our results indicate that simpler hierarchical models are valid in situations with few studies or sparse data. For synthesis of sensitivity and specificity, univariate random effects logistic regression models are appropriate when a bivariate model cannot be fitted. Alternatively, an HSROC model that assumes a symmetric SROC curve (by excluding the shape parameter) can be used if the HSROC model is the chosen meta-analytic approach. In the absence of heterogeneity, fixed effect equivalent of the models can be applied.
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Affiliation(s)
- Yemisi Takwoingi
- 1 Public Health, Epidemiology and Biostatistics, University of Birmingham, Edgbaston, Birmingham, UK
| | - Boliang Guo
- 2 School of Medicine, University of Nottingham, Nottingham, UK
| | - Richard D Riley
- 3 Research Institute of Primary Care and Health Sciences, Keele University, Staffordshire, UK
| | - Jonathan J Deeks
- 1 Public Health, Epidemiology and Biostatistics, University of Birmingham, Edgbaston, Birmingham, UK
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28
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Diaz M. Performance measures of the bivariate random effects model for meta-analyses of diagnostic accuracy. Comput Stat Data Anal 2015. [DOI: 10.1016/j.csda.2014.09.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Hoyer A, Kuss O. Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas. Stat Med 2015; 34:1912-24. [PMID: 25712874 DOI: 10.1002/sim.6463] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2014] [Revised: 02/10/2015] [Accepted: 02/12/2015] [Indexed: 11/12/2022]
Abstract
In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples.
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Affiliation(s)
- A Hoyer
- German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Duesseldorf, Institute for Biometry and Epidemiology, Duesseldorf, Germany
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Chen C, Wakefield J, Lumely T. The use of sampling weights in Bayesian hierarchical models for small area estimation. Spat Spatiotemporal Epidemiol 2014; 11:33-43. [PMID: 25457595 DOI: 10.1016/j.sste.2014.07.002] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2014] [Revised: 05/22/2014] [Accepted: 07/12/2014] [Indexed: 10/24/2022]
Abstract
Hierarchical modeling has been used extensively for small area estimation. However, design weights that are required to reflect complex surveys are rarely considered in these models. We develop computationally efficient, Bayesian spatial smoothing models that acknowledge the design weights. Computation is carried out using the integrated nested Laplace approximation, which is fast. An extensive simulation study is presented that considers the effects of non-response and non-random selection of individuals, allowing examination of the impact of ignoring the design weights and the benefits of spatial smoothing. The results show that, when compared with standard approaches, mean squared error can be greatly reduced with the proposed methods. Bias reduction occurs through the inclusion of the design weights, with variance reduction being achieved through hierarchical smoothing. We analyze data from the Washington State 2006 Behavioral Risk Factor Surveillance System. The models are easily and quickly fitted within the R environment, using existing packages.
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Affiliation(s)
- Cici Chen
- Department of Biostatistics, Brown University, USA.
| | - Jon Wakefield
- Department of Statistics, University of Washington, USA; Department Biostatistics, University of Washington, USA.
| | - Thomas Lumely
- Department of Statistics, University of Auckland, New Zealand
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31
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Eusebi P, Reitsma JB, Vermunt JK. Latent class bivariate model for the meta-analysis of diagnostic test accuracy studies. BMC Med Res Methodol 2014; 14:88. [PMID: 25015209 PMCID: PMC4105799 DOI: 10.1186/1471-2288-14-88] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 05/08/2014] [Indexed: 11/10/2022] Open
Abstract
Background Several types of statistical methods are currently available for the meta-analysis of studies on diagnostic test accuracy. One of these methods is the Bivariate Model which involves a simultaneous analysis of the sensitivity and specificity from a set of studies. In this paper, we review the characteristics of the Bivariate Model and demonstrate how it can be extended with a discrete latent variable. The resulting clustering of studies yields additional insight into the accuracy of the test of interest. Methods A Latent Class Bivariate Model is proposed. This model captures the between-study variability in sensitivity and specificity by assuming that studies belong to one of a small number of latent classes. This yields both an easier to interpret and a more precise description of the heterogeneity between studies. Latent classes may not only differ with respect to the average sensitivity and specificity, but also with respect to the correlation between sensitivity and specificity. Results The Latent Class Bivariate Model identifies clusters of studies with their own estimates of sensitivity and specificity. Our simulation study demonstrated excellent parameter recovery and good performance of the model selection statistics typically used in latent class analysis. Application in a real data example on coronary artery disease showed that the inclusion of latent classes yields interesting additional information. Conclusions Our proposed new meta-analysis method can lead to a better fit of the data set of interest, less biased estimates and more reliable confidence intervals for sensitivities and specificities. But even more important, it may serve as an exploratory tool for subsequent sub-group meta-analyses.
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Affiliation(s)
- Paolo Eusebi
- Department of Epidemiology, Regional Health Authority of Umbria, Via Mario Angeloni, 61, 06124 Perugia, Italy.
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Muff S, Riebler A, Held L, Rue H, Saner P. Bayesian analysis of measurement error models using integrated nested Laplace approximations. J R Stat Soc Ser C Appl Stat 2014. [DOI: 10.1111/rssc.12069] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
| | - Andrea Riebler
- Norwegian University of Science and Technology; Trondheim Norway
| | | | - Håvard Rue
- Norwegian University of Science and Technology; Trondheim Norway
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Connelly CF, Wakefield J, Akey JM. Evolution and genetic architecture of chromatin accessibility and function in yeast. PLoS Genet 2014; 10:e1004427. [PMID: 24992477 PMCID: PMC4081003 DOI: 10.1371/journal.pgen.1004427] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Accepted: 04/23/2014] [Indexed: 01/23/2023] Open
Abstract
Chromatin accessibility is an important functional genomics phenotype that influences transcription factor binding and gene expression. Genome-scale technologies allow chromatin accessibility to be mapped with high-resolution, facilitating detailed analyses into the genetic architecture and evolution of chromatin structure within and between species. We performed Formaldehyde-Assisted Isolation of Regulatory Elements sequencing (FAIRE-Seq) to map chromatin accessibility in two parental haploid yeast species, Saccharomyces cerevisiae and Saccharomyces paradoxus and their diploid hybrid. We show that although broad-scale characteristics of the chromatin landscape are well conserved between these species, accessibility is significantly different for 947 regions upstream of genes that are enriched for GO terms such as intracellular transport and protein localization exhibit. We also develop new statistical methods to investigate the genetic architecture of variation in chromatin accessibility between species, and find that cis effects are more common and of greater magnitude than trans effects. Interestingly, we find that cis and trans effects at individual genes are often negatively correlated, suggesting widespread compensatory evolution to stabilize levels of chromatin accessibility. Finally, we demonstrate that the relationship between chromatin accessibility and gene expression levels is complex, and a significant proportion of differences in chromatin accessibility might be functionally benign.
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Affiliation(s)
- Caitlin F. Connelly
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Jon Wakefield
- Department of Statistics, University of Washington, Seattle, Washington, United States of America
| | - Joshua M. Akey
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
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Kang SY, McGree J, Mengersen K. The choice of spatial scales and spatial smoothness priors for various spatial patterns. Spat Spatiotemporal Epidemiol 2014; 10:11-26. [PMID: 25113587 DOI: 10.1016/j.sste.2014.05.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2014] [Revised: 04/17/2014] [Accepted: 05/29/2014] [Indexed: 11/26/2022]
Abstract
Given the drawbacks for using geo-political areas in mapping outcomes unrelated to geo-politics, a compromise is to aggregate and analyse data at the grid level. This has the advantage of allowing spatial smoothing and modelling at a biologically or physically relevant scale. This article addresses two consequent issues: the choice of the spatial smoothness prior and the scale of the grid. Firstly, we describe several spatial smoothness priors applicable for grid data and discuss the contexts in which these priors can be employed based on different aims. Two such aims are considered, i.e., to identify regions with clustering and to model spatial dependence in the data. Secondly, the choice of the grid size is shown to depend largely on the spatial patterns. We present a guide on the selection of spatial scales and smoothness priors for various point patterns based on the two aims for spatial smoothing.
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Affiliation(s)
- Su Yun Kang
- Mathematical Sciences School, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia; CRC for Spatial Information, 204 Lygon Street, Carlton, Victoria 3053, Australia.
| | - James McGree
- Mathematical Sciences School, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia; CRC for Spatial Information, 204 Lygon Street, Carlton, Victoria 3053, Australia
| | - Kerrie Mengersen
- Mathematical Sciences School, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia; CRC for Spatial Information, 204 Lygon Street, Carlton, Victoria 3053, Australia
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35
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Affiliation(s)
- Elena Kulinskaya
- School of Computing Sciences; University of East Anglia; Norwich NR4 7TJ UK
| | - Stephan Morgenthaler
- Ecole polytechnique fédérale de Lausanne (EPFL); Station 8, 1015 Lausanne Switzerland
| | - Robert G. Staudte
- Department of Statistics and Mathematics; La Trobe University; Melbourne, VIC 3086 Australia
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Blangiardo M, Cameletti M, Baio G, Rue H. Spatial and spatio-temporal models with R-INLA. Spat Spatiotemporal Epidemiol 2013; 7:39-55. [DOI: 10.1016/j.sste.2013.07.003] [Citation(s) in RCA: 116] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Byrne AL, Bennett MH, Pace NL, Thomas P. Peripheral venous blood gas analysis versus arterial blood gas analysis for the diagnosis of respiratory failure and metabolic disturbance in adults. THE COCHRANE DATABASE OF SYSTEMATIC REVIEWS 2013. [DOI: 10.1002/14651858.cd010841] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Anthony L Byrne
- St Vincents Hospital; Heart Lung Clinic; Xavier building Victoria Street Darlinghurst NSW Australia 2010
| | - Michael H Bennett
- Prince of Wales Clinical School, University of NSW; Department of Anaesthesia; Sydney NSW Australia
| | - Nathan L Pace
- University of Utah; Department of Anesthesiology; 3C444 SOM 30 North 1900 East Salt Lake City UT USA 84132-2304
| | - Paul Thomas
- Prince of Wales Hospital; Department of Respiratory Medicine; Level 2 Campus Centre Barker Street, Randwick Sydney Australia 2031
- University of New South Wales; Sydney Australia
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Kuss O, Hoyer A, Solms A. Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas. Stat Med 2013; 33:17-30. [PMID: 23873593 DOI: 10.1002/sim.5909] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2012] [Accepted: 06/15/2013] [Indexed: 11/06/2022]
Abstract
There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration.
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Affiliation(s)
- Oliver Kuss
- Institute of Medical Epidemiology, Biostatistics, and Informatics, University of Halle-Wittenberg, Halle (Saale), Germany
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40
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Roadmap to determine the point mutations involved in cardiomyopathy disorder: A Bayesian approach. Gene 2013; 519:34-40. [DOI: 10.1016/j.gene.2013.01.056] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2012] [Revised: 12/31/2012] [Accepted: 01/27/2013] [Indexed: 11/18/2022]
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41
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Lee D, Mitchell R. Locally adaptive spatial smoothing using conditional auto-regressive models. J R Stat Soc Ser C Appl Stat 2013. [DOI: 10.1111/rssc.12009] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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42
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Blangiardo M, Cameletti M, Baio G, Rue H. Spatial and spatio-temporal models with R-INLA. Spat Spatiotemporal Epidemiol 2013; 4:33-49. [DOI: 10.1016/j.sste.2012.12.001] [Citation(s) in RCA: 158] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2012] [Revised: 11/28/2012] [Accepted: 12/05/2012] [Indexed: 10/27/2022]
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Warschkow R, Ukegjini K, Tarantino I, Steffen T, Müller SA, Schmied BM, Marti L. Diagnostic study and meta-analysis of C-reactive protein as a predictor of postoperative inflammatory complications after pancreatic surgery. JOURNAL OF HEPATO-BILIARY-PANCREATIC SCIENCES 2013; 19:492-500. [PMID: 22038499 DOI: 10.1007/s00534-011-0462-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE Although C-reactive protein (CRP) can be measured by a standard blood test, its diagnostic value for distinguishing patients with inflammatory complications after pancreatic surgery from patients with normal postoperative inflammatory responses has not been adequately investigated. This study aimed to assess the diagnostic accuracy of CRP levels for the occurrence of postoperative inflammatory complications after pancreatic surgery. METHODS Clinical data and CRP levels measured in 280 patients after pancreatic surgeries (performed between 1998 and 2010) until postoperative day 10 (POD 10) were retrospectively analyzed. Using the receiver operating characteristic method, diagnostic accuracy was evaluated by an area under the curve (AUC) analysis. Furthermore, the results of the present study were compared to previously published reports by applying diagnostic meta-analysis techniques. RESULTS The 30-day mortality rate was 3.9% (95% CI 2.1-7.0%). Inflammatory complications occurred in 153 of 280 patients (54.6%; 95% CI 48.8-60.4%). On POD 4, the AUC was 0.67 (95% CI 0.58-0.76). The highest diagnostic accuracy was observed on POD 7 (AUC 0.77; 95% CI 0.68-0.85). In a diagnostic meta-analysis that included two additional studies, the diagnostic sensitivity on POD 4 was 0.63 (95% CI 0.50-0.76), and the specificity was 0.79 (95% CI 0.71-0.88). The highest sensitivity occurred on POD 6 (0.75; 95% CI 0.68-0.82). Considerable statistical heterogeneity was observed in the analysis of PODs 3, 4 and 5. CONCLUSION According to this limited evidence, CRP levels had a low to moderate diagnostic accuracy. Large, blinded studies are warranted for a more precise estimation of CRP's diagnostic value.
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Affiliation(s)
- Rene Warschkow
- Department of Surgery, Kantonsspital St. Gallen, 9007 St. Gallen, Switzerland.
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Hinchliffe SR, Crowther MJ, Phillips RS, Sutton AJ. Using meta-analysis to inform the design of subsequent studies of diagnostic test accuracy. Res Synth Methods 2012; 4:156-68. [DOI: 10.1002/jrsm.1066] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2011] [Revised: 10/10/2012] [Accepted: 10/12/2012] [Indexed: 11/11/2022]
Affiliation(s)
- Sally R. Hinchliffe
- Biostatistics Group, Department of Health Sciences; University of Leicester; Leicester; UK
| | - Michael J. Crowther
- Biostatistics Group, Department of Health Sciences; University of Leicester; Leicester; UK
| | - Robert S. Phillips
- Regional Department of Paediatric Haematology/Oncology; St James's Hospital; Leeds; UK
| | - Alex J. Sutton
- Biostatistics Group, Department of Health Sciences; University of Leicester; Leicester; UK
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Safe and early discharge after colorectal surgery due to C-reactive protein: a diagnostic meta-analysis of 1832 patients. Ann Surg 2012; 256:245-50. [PMID: 22735714 DOI: 10.1097/sla.0b013e31825b60f0] [Citation(s) in RCA: 129] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To assess the predictive value of C-reactive protein (CRP) level for postoperative infectious complications after colorectal surgery. BACKGROUND Postoperative infectious complications after colorectal surgery are frequent and associated with relevant short- and long-term sequelae. Therefore, the identification of a diagnostic tool for early recognition of postoperative infectious complications is of cardinal importance. METHODS A meta-analysis was performed for diagnostic studies evaluating CRP as a predictor for postoperative infectious complications on days 1 to 5 after colorectal surgery. RESULTS Six studies including a total of 1832 patients were identified. The best performance of CRP to predict postoperative infectious complications was on postoperative day 4, on which the mean CRP cutoff value was 135 mg/L (SD: 10 mg/L), the pooled sensitivity 68% (95% CI: 57%-79%), the specificity 83% (95% CI: 77%-90%) and the negative predictive value 89% (95% CI: 87%-92%). The pooled area under the receiver operating characteristic curve was 0.81 (95% CI: 0.73-0.89). CONCLUSIONS This diagnostic meta-analysis of 1832 patients--the first in the literature--provides compelling evidence that C-reactive protein on postoperative day 4 has a high negative predictive value for infectious complications of 89%. Therefore, CRP measurement allows safe and early discharge of selected patients after colorectal surgery.
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Riebler A, Held L, Rue H. Estimation and extrapolation of time trends in registry data—Borrowing strength from related populations. Ann Appl Stat 2012. [DOI: 10.1214/11-aoas498] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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47
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Willis BH, Quigley M. Uptake of newer methodological developments and the deployment of meta-analysis in diagnostic test research: a systematic review. BMC Med Res Methodol 2011; 11:27. [PMID: 21401947 PMCID: PMC3065444 DOI: 10.1186/1471-2288-11-27] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2010] [Accepted: 03/14/2011] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND The last decade has seen a number of methodological developments in meta-analysis of diagnostic test studies. However, it is unclear whether such developments have permeated the wider research community and on which applications they are being deployed. The objective was to assess the uptake and deployment of the main methodological developments in the meta-analysis of diagnostic tests, and identify the tests and target disorders most commonly evaluated by meta-analysis. METHODS Design--systematic review. Data Sources--Medline, EMBASE, CINAHL, Cochrane, PsychInfo, Global health, HMIC, and AMED were searched for studies published before 31st December 2008. Selection criteria--studies were included if they satisfied all of the following: evaluated a diagnostic test; measured test performance; searched two or more databases; stated search terms and inclusion criteria; used a statistical method to summarise performance. Data extraction--included the following data items: year; test; reference standard; target disorder; setting; statistical and quality methods. RESULTS 236 studies were included. Over the last 5 years the number of meta-analyses published has increased, but the uptake of new statistical methods lags behind. Pooling the sensitivity and specificity and using the SROC remain the preferred methods for analysis in 70% of studies, with the bivariate random effects and HSROC model being used in only 22% and 5% of studies respectively. In contrast, between 2006 and 2008 the QUADAS tool was used in 40% of studies. Broadly, radiological imaging was the most frequent category of tests analysed (36%), with cancer (22%) and infection (21%) being the most common categories of target disorder. Nearly 80% of tests analysed were those normally used in specialist settings. CONCLUSION Although quality assessment in meta-analyses has improved with the introduction of QUADAS, uptake of the newer statistical methods is still lagging behind. Furthermore, the focus of secondary research seems to be in evaluating specialist tests in specialist settings, in contrast to the more routine tests and settings encountered in the majority of clinical practice.
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Affiliation(s)
- Brian H Willis
- Biostatistics, University of Manchester, Jean McFarlane building, Oxford Road, Manchester, M13 9PL, UK
| | - Muireann Quigley
- Centre for Social Ethics and Policy, University of Manchester, Williamson building, Oxford Road, Manchester, M13 9PL, UK
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Jackson D, Riley R, White IR. Multivariate meta-analysis: potential and promise. Stat Med 2011; 30:2481-98. [PMID: 21268052 PMCID: PMC3470931 DOI: 10.1002/sim.4172] [Citation(s) in RCA: 262] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2010] [Accepted: 11/01/2010] [Indexed: 01/14/2023]
Abstract
The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.
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Verde PE. Meta-analysis of diagnostic test data: A bivariate Bayesian modeling approach. Stat Med 2010; 29:3088-102. [DOI: 10.1002/sim.4055] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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50
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Lee A, Herkner H, Hovhannisyan K, Pace NL. Airway physical examination tests for detection of difficult airway management in apparently normal patients. THE COCHRANE DATABASE OF SYSTEMATIC REVIEWS 2010. [DOI: 10.1002/14651858.cd008874] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Anna Lee
- The Chinese University of Hong Kong; Department of Anaesthesia and Intensive Care; Prince of Wales Hospital Shatin New Territories Hong Kong
| | - Harald Herkner
- Medical University of Vienna; Department of Emergency Medicine; Vienna General Hospital; Währinger Gürtel 18-20 / 6D Vienna Austria 1090
| | - Karen Hovhannisyan
- Rigshospitalet; The Cochrane Anaesthesia Review Group; Blegdamsvej 9, Afsnit 3342, rum 52 Copenhagen Denmark 2100
| | - Nathan Leon Pace
- University of Utah; Department of Anesthesiology; 3C444 SOM 30 North 1900 East Salt Lake City UT USA 84132-2304
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