Browsing by Subject "Meta-Analysis as Topic"

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    ItemOpen Access
    A brief history of research synthesis.
    (Eval Health Prof, 2002-03) Chalmers, Iain; Hedges, Larry V; Cooper, Harris
    Science is supposed to be cumulative, but scientists only rarely cumulate evidence scientifically. This means that users of research evidence have to cope with a plethora of reports of individual studies with no systematic attempt made to present new results in the context of similar studies. Although the need to synthesize research evidence has been recognized for well over two centuries, explicit methods for this form of research were not developed until the 20th century. The development of methods to reduce statistical imprecision using quantitative synthesis (meta-analysis) preceded the development of methods to reduce biases, the latter only beginning to receive proper attention during the last quarter of the 20th century. In this article, the authors identify some of the trends and highlights in this history, to which researchers in the physical, natural, and social sciences have all contributed, and speculate briefly about the "future history" of research synthesis.
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    Associations of PI3KR1 and mTOR polymorphisms with esophageal squamous cell carcinoma risk and gene-environment interactions in Eastern Chinese populations.
    (Scientific reports, 2015-01) Zhu, Jinhong; Wang, Mengyun; Zhu, Meiling; He, Jin; Wang, Jiu-Cun; Jin, Li; Wang, Xiao-Feng; Xiang, Jia-Qing; Wei, Qingyi
    Single nucleotide polymorphisms (SNPs) in the PI3K/PTEN/AKT/mTOR signaling pathway may contribute to carcinogenesis. We genotyped five potentially functional PIK3R1 and mTOR SNPs in 1116 esophageal squamous cell cancer (ESCC) patients and 1117 cancer-free controls to assess their associations with ESCC risk. We observed no association with ESCC risk for any of the selected SNPs. However, the combined analysis of these SNPs revealed that subjects with one-to-three risk genotypes had an increased ESCC risk. Stratified analysis by body mass index (BMI) found that ESCC risk was significantly associated with each of three mTOR SNPs among subjects with BMI < 25.0. Specifically, we found that subjects carrying ≥ 1 risk genotypes had significantly increased ESCC risk, particularly for males, ever-smokers, ever-drinkers, and those with age > 60, or BMI < 25.0. Moreover, three mTOR haplotypes were associated with an increase in ESCC risk. Our meta-analysis of mTOR rs2295080 and cancer risk provided further evidence that mTOR SNPs might modulate cancer susceptibility. In this population, such risk effects might be modified by other risk factors, highlighting the importance of gene-environment interaction in esophageal carcinogenesis. Additional, larger studies are warranted to validate our findings.
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    Automatic identification of variables in epidemiological datasets using logic regression.
    (BMC medical informatics and decision making, 2017-04) Lorenz, Matthias W; Abdi, Negin Ashtiani; Scheckenbach, Frank; Pflug, Anja; Bülbül, Alpaslan; Catapano, Alberico L; Agewall, Stefan; Ezhov, Marat; Bots, Michiel L; Kiechl, Stefan; Orth, Andreas; PROG-IMT study group

    Background

    For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable.

    Methods

    For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated.

    Results

    In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables.

    Conclusions

    We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.
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    Bumps and bridges on the road to responsible sharing of clinical trial data.
    (Clin Trials, 2014-02) Berlin, Jesse A; Morris, Sandra; Rockhold, Frank; Askie, Lisa; Ghersi, Davina; Waldstreicher, Joanne
    BACKGROUND: Sharing data from clinical trials could assist with the advancement of science and medicine, potentially providing a better understanding of both the benefits and risks of medicines and other treatments. Sharing data also allows for questions to be addressed at the meta-analysis level that cannot be addressed within individual studies. PURPOSE: In this article, we offer some practical recommendations that will allow researchers to readily combine datasets from different studies and sources, thereby enabling meta-analyses that could have significant impact on advancing medicine. METHODS: The authors relied on their collective experience in the conduct and reporting of clinical trials to define the areas of potential concern related to responsible sharing of clinical trial data. We conducted a review of the literature and engaged in an iterative consensus-building process. RESULTS: To further the goal of responsible sharing of clinical trial data, collaboration on a consistent set of data standards and methods across both industry and academia is sorely needed. Protection of participant privacy is a paramount principle. The additional questions of who maintains, funds, and oversees databases of participant-level data will be important to resolve. Requiring researchers to register their requests for participant-level data and to provide details of their intended research would allow others to evaluate the proposed research plan, consistent with the principles of science and transparency. LIMITATIONS: The recommendations represent the views of the individual authors. We recognize that other approaches to data sharing that have been advocated are also based on sound ethical and scientific principles.
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    Effect of SGLT2 Inhibitors on Stroke and Atrial Fibrillation in Diabetic Kidney Disease: Results From the CREDENCE Trial and Meta-Analysis.
    (Stroke, 2021-05) Zhou, Zien; Jardine, Meg J; Li, Qiang; Neuen, Brendon L; Cannon, Christopher P; de Zeeuw, Dick; Edwards, Robert; Levin, Adeera; Mahaffey, Kenneth W; Perkovic, Vlado; Neal, Bruce; Lindley, Richard I; CREDENCE Trial Investigators*

    Background and purpose

    Chronic kidney disease with reduced estimated glomerular filtration rate or elevated albuminuria increases risk for ischemic and hemorrhagic stroke. This study assessed the effects of sodium glucose cotransporter 2 inhibitors (SGLT2i) on stroke and atrial fibrillation/flutter (AF/AFL) from CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) and a meta-analysis of large cardiovascular outcome trials (CVOTs) of SGLT2i in type 2 diabetes mellitus.

    Methods

    CREDENCE randomized 4401 participants with type 2 diabetes mellitus and chronic kidney disease to canagliflozin or placebo. Post hoc, we estimated effects on fatal or nonfatal stroke, stroke subtypes, and intermediate markers of stroke risk including AF/AFL. Stroke and AF/AFL data from 3 other completed large CVOTs and CREDENCE were pooled using random-effects meta-analysis.

    Results

    In CREDENCE, 142 participants experienced a stroke during follow-up (10.9/1000 patient-years with canagliflozin, 14.2/1000 patient-years with placebo; hazard ratio [HR], 0.77 [95% CI, 0.55-1.08]). Effects by stroke subtypes were: ischemic (HR, 0.88 [95% CI, 0.61-1.28]; n=111), hemorrhagic (HR, 0.50 [95% CI, 0.19-1.32]; n=18), and undetermined (HR, 0.54 [95% CI, 0.20-1.46]; n=17). There was no clear effect on AF/AFL (HR, 0.76 [95% CI, 0.53-1.10]; n=115). The overall effects in the 4 CVOTs combined were: total stroke (HRpooled, 0.96 [95% CI, 0.82-1.12]), ischemic stroke (HRpooled, 1.01 [95% CI, 0.89-1.14]), hemorrhagic stroke (HRpooled, 0.50 [95% CI, 0.30-0.83]), undetermined stroke (HRpooled, 0.86 [95% CI, 0.49-1.51]), and AF/AFL (HRpooled, 0.81 [95% CI, 0.71-0.93]). There was evidence that SGLT2i effects on total stroke varied by baseline estimated glomerular filtration rate (P=0.01), with protection in the lowest estimated glomerular filtration rate (<45 mL/min/1.73 m2]) subgroup (HRpooled, 0.50 [95% CI, 0.31-0.79]).

    Conclusions

    Although we found no clear effect of SGLT2i on total stroke in CREDENCE or across trials combined, there was some evidence of benefit in preventing hemorrhagic stroke and AF/AFL, as well as total stroke for those with lowest estimated glomerular filtration rate. Future research should focus on confirming these data and exploring potential mechanisms. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02065791.
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    Individual patient data meta-analysis of self-monitoring of blood pressure (BP-SMART): a protocol.
    (BMJ open, 2015-09) Tucker, Katherine L; Sheppard, James P; Stevens, Richard; Bosworth, Hayden B; Bove, Alfred; Bray, Emma P; Godwin, Marshal; Green, Beverly; Hebert, Paul; Hobbs, FD Richard; Kantola, Ilkka; Kerry, Sally; Magid, David J; Mant, Jonathan; Margolis, Karen L; McKinstry, Brian; Omboni, Stefano; Ogedegbe, Olugbenga; Parati, Gianfranco; Qamar, Nashat; Varis, Juha; Verberk, Willem; Wakefield, Bonnie J; McManus, Richard J

    Introduction

    Self-monitoring of blood pressure is effective in reducing blood pressure in hypertension. However previous meta-analyses have shown a considerable amount of heterogeneity between studies, only part of which can be accounted for by meta-regression. This may be due to differences in design, recruited populations, intervention components or results among patient subgroups. To further investigate these differences, an individual patient data (IPD) meta-analysis of self-monitoring of blood pressure will be performed.

    Methods and analysis

    We will identify randomised trials that have compared patients with hypertension who are self-monitoring blood pressure with those who are not and invite trialists to provide IPD including clinic and/or ambulatory systolic and diastolic blood pressure at baseline and all follow-up points where both intervention and control groups were measured. Other data requested will include measurement methodology, length of follow-up, cointerventions, baseline demographic (age, gender) and psychosocial factors (deprivation, quality of life), setting, intensity of self-monitoring, self-monitored blood pressure, comorbidities, lifestyle factors (weight, smoking) and presence or not of antihypertensive treatment. Data on all available patients will be included in order to take an intention-to-treat approach. A two-stage procedure for IPD meta-analysis, stratified by trial and taking into account age, sex, diabetes and baseline systolic BP will be used. Exploratory subgroup analyses will further investigate non-linear relationships between the prespecified variables. Sensitivity analyses will assess the impact of trials which have and have not provided IPD.

    Ethics and dissemination

    This study does not include identifiable data. Results will be disseminated in a peer-reviewed publication and by international conference presentations.

    Conclusions

    IPD analysis should help the understanding of which self-monitoring interventions for which patient groups are most effective in the control of blood pressure.
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    Reporting standards for literature searches and report inclusion criteria: making research syntheses more transparent and easy to replicate.
    (Res Synth Methods, 2015-03) Atkinson, Kayla M; Koenka, Alison C; Sanchez, Carmen E; Moshontz, Hannah; Cooper, Harris
    A complete description of the literature search, including the criteria used for the inclusion of reports after they have been located, used in a research synthesis or meta-analysis is critical if subsequent researchers are to accurately evaluate and reproduce a synthesis' methods and results. Based on previous guidelines and new suggestions, we present a set of focused and detailed standards for reporting the methods used in a literature search. The guidelines cover five search strategies: reference database searches, journal and bibliography searches, searches of the reference lists of reports, citation searches, and direct contact searches. First, we bring together all the unique recommendations made in existing guidelines for research synthesis. Second, we identify gaps in reporting standards for search strategies. Third, we address these gaps by providing new reporting recommendations. Our hope is to facilitate successful evaluation and replication of research synthesis results.
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    The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data.
    (Translational psychiatry, 2011-10-18) Middeldorp, CM; de Moor, MHM; McGrath, LM; Gordon, SD; Blackwood, DH; Costa, PT; Terracciano, A; Krueger, RF; de Geus, EJC; Nyholt, DR; Tanaka, T; Esko, T; Madden, PAF; Derringer, J; Amin, N; Willemsen, G; Hottenga, J-J; Distel, MA; Uda, M; Sanna, S; Spinhoven, P; Hartman, CA; Ripke, S; Sullivan, PF; Realo, A; Allik, J; Heath, AC; Pergadia, ML; Agrawal, A; Lin, P; Grucza, RA; Widen, E; Cousminer, DL; Eriksson, JG; Palotie, A; Barnett, JH; Lee, PH; Luciano, M; Tenesa, A; Davies, G; Lopez, LM; Hansell, NK; Medland, SE; Ferrucci, L; Schlessinger, D; Montgomery, GW; Wright, MJ; Aulchenko, YS; Janssens, ACJW; Oostra, BA; Metspalu, A; Abecasis, GR; Deary, IJ; Räikkönen, K; Bierut, LJ; Martin, NG; Wray, NR; van Duijn, CM; Smoller, JW; Penninx, BWJH; Boomsma, DI
    The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.