Logistic regression in meta-analysis using aggregate data

2000 ◽  
Vol 27 (4) ◽  
pp. 411-424 ◽  
Author(s):  
Bei-Hung Chang ◽  
Stuart Lipsitz ◽  
Christine Waternaux
Keyword(s):  
Logistic Regression ◽  
Meta Analysis ◽  
Aggregate Data

scholarly journals Comparing the use of aggregate data and various methods of integrating individual patient data to network meta-analysis and its application to first-line ART

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Steve Kanters ◽  
Mohammad Ehsanul Karim ◽  
Kristian Thorlund ◽  
Aslam H. Anis ◽  
Michael Zoratti ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Evidence Base ◽  
Aggregate Data ◽  
World Health ◽  
Coefficient Estimates ◽  
Two Stage ◽  
Individual Patient Level ◽  
One Stage ◽  
Meta Regression ◽  
Empirical Priors

Abstract Background The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. Methods Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) – the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. Results IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. Conclusions Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

scholarly journals Incorporating single-arm studies in meta-analysis of randomised controlled trials: a simulation study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Janharpreet Singh ◽  
Keith R. Abrams ◽  
Sylwia Bujkiewicz
Keyword(s):  
Simulation Study ◽  
Randomised Controlled Trials ◽  
Meta Analysis ◽  
Health Technology ◽  
Small Error ◽  
Aggregate Data ◽  
Controlled Trials ◽  
Real World Data ◽  
Study Heterogeneity ◽  
Randomised Controlled

Abstract Background Use of real world data (RWD) from non-randomised studies (e.g. single-arm studies) is increasingly being explored to overcome issues associated with data from randomised controlled trials (RCTs). We aimed to compare methods for pairwise meta-analysis of RCTs and single-arm studies using aggregate data, via a simulation study and application to an illustrative example. Methods We considered contrast-based methods proposed by Begg & Pilote (1991) and arm-based methods by Zhang et al (2019). We performed a simulation study with scenarios varying (i) the proportion of RCTs and single-arm studies in the synthesis (ii) the magnitude of bias, and (iii) between-study heterogeneity. We also applied methods to data from a published health technology assessment (HTA), including three RCTs and 11 single-arm studies. Results Our simulation study showed that the hierarchical power and commensurate prior methods by Zhang et al provided a consistent reduction in uncertainty, whilst maintaining over-coverage and small error in scenarios where there was limited RCT data, bias and differences in between-study heterogeneity between the two sets of data. The contrast-based methods provided a reduction in uncertainty, but performed worse in terms of coverage and error, unless there was no marked difference in heterogeneity between the two sets of data. Conclusions The hierarchical power and commensurate prior methods provide the most robust approach to synthesising aggregate data from RCTs and single-arm studies, balancing the need to account for bias and differences in between-study heterogeneity, whilst reducing uncertainty in estimates. This work was restricted to considering a pairwise meta-analysis using aggregate data.

scholarly journals Review of Methods for Combining Individual and Aggregate Data in a Meta-Analysis

2016 ◽  
Vol 19 (7) ◽  
pp. A362
Author(s):  
R Kapso Kapnang ◽  
K Thokagevistk ◽  
A Vataire ◽  
S Aballéa
Keyword(s):  
Meta Analysis ◽  
Aggregate Data

Meta-analysis of individual patient data versus aggregate data from longitudinal clinical trials

2009 ◽  
Vol 6 (1) ◽  
pp. 16-27 ◽  
Author(s):  
Ashley P Jones ◽  
Richard D Riley ◽  
Paula R Williamson ◽  
Anne Whitehead
Keyword(s):  
Clinical Trials ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Patient Data ◽  
Aggregate Data

scholarly journals Association between genetic polymorphisms and osteonecrosis in steroid treatment populations: a detailed stratified and dose-response meta-analysis

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
Jun Yang ◽  
Ming Jing ◽  
Xiaoge Yang
Keyword(s):  
Logistic Regression ◽  
Renal Transplant ◽  
Femoral Head ◽  
Protective Effect ◽  
Dose Response ◽  
Meta Analysis ◽  
Steroid Treatment ◽  
Dose Effect ◽  
Cumulative Dosage ◽  
Mutation Carriers

Abstract Steroid treatment has become recognized as an important risk factor for avascular osteonecrosis of the femoral head. However, not all patients who receive long-term, high-dose steroids develop osteonecrosis, indicating that there are individual differences in occurrence. We explored the relationship between polymorphisms and steroid-induced osteonecrosis of the femoral head (SONFH) incidence with variables. We used a multilevel mixed-effects logistic regression model, which is an expansion of logistic regression, for each type of steroid, primary disease, drug dose, applied duration, and single-nucleotide polymorphism (SNP). We also conducted a dose-response meta-analysis to analyze the cumulative dosage and SONFH risk in mutation carriers. There were significant correlations between the ABCB1 rs1045642 mutant and SONFH in the prednisone-use and methylprednisolone/prednisone-use populations. The ABCB1 rs2032582 mutant homozygote had a protective effect in the methylprednisolone/prednisolone renal transplant population. For ApoB rs693, mutation increased the incidence of SONFH in prednisone-use and methylprednisolone/prednisolone-use populations and renal transplant patients. For ApoB rs1042031, mutation increased the risk of SONFH in the prednisone-use population. The PAI-1 rs1799768 mutation had a protective effect on the SONFH risk prednisone-use and renal transplant populations. ABCB1 rs1045642 mutations have a protective effect against SONFH, and ApoB rs693 and rs1042031 increase the SONFH risk. Cumulative dosage and treatment duration had little effect on the results. In addition, there was a dose-effect correlation in ABCB1 rs1045642 and rs2032582 mutation carriers.

Lateral sinus floor elevation without grafting materials. Individual- and aggregate-data meta-analysis

2018 ◽  
Vol 46 (9) ◽  
pp. 1616-1624
Author(s):  
Victor Dongo ◽  
Nadine von Krockow ◽  
Paulo Ricardo Saquete Martins-Filho ◽  
Paul Weigl
Keyword(s):  
Meta Analysis ◽  
Aggregate Data ◽  
Lateral Sinus ◽  
Sinus Floor Elevation ◽  
Sinus Floor ◽  
Grafting Materials

scholarly journals Cadmium Is Associated with Type 2 Diabetes in a Superfund Site Lead Smelter Community in Dallas, Texas

2020 ◽  
Vol 17 (12) ◽  
pp. 4558
Author(s):  
Bert B. Little ◽  
Robert Reilly ◽  
Brad Walsh ◽  
Giang T. Vu
Keyword(s):  
Type 2 Diabetes ◽  
Logistic Regression ◽  
Fixed Effects ◽  
Smoking Status ◽  
Meta Analysis ◽  
Two Phase ◽  
Lead Smelter ◽  
Increased Risk ◽  
Cd Exposure

Objective: To test the hypothesis that cadmium (Cd) exposure is associated with type 2 diabetes mellitus (T2DM). Materials and Methods: A two-phase health screening (physical examination and laboratory tests) was conducted in a lead smelter community following a Superfund Cleanup. Participants were African Americans aged >19 years to <89 years. Multiple logistic regression was used to analyze T2DM regressed on blood Cd level and covariates: body mass index (BMI), heavy metals (Ar, Cd, Hg, Pb), duration of residence, age, smoking status, and sex. Results: Of 875 subjects environmentally exposed to Cd, 55 were occupationally exposed to by-products of lead smelting and 820 were community residents. In addition, 109 T2DM individuals lived in the community for an average of 21.0 years, and 766 non-T2DM individuals for 19.0 years. T2DM individuals (70.3%) were >50 years old. Blood Cd levels were higher among T2DM subjects (p < 0.006) compared to non-T2DM individuals. Logistic regression of T2DM status identified significant predictors: Cd level (OR = 1.85; 95% CI: 1.14–2.99, p < 0.01), age >50 years (OR = 3.10; 95% CI: 1.91–5.02, p < 0.0001), and BMI (OR = 1.07; CI: 1.04–1.09, 0.0001). In meta-analysis of 12 prior studies and this one, T2DM risk was OR = 1.09 (95% CI: 1.03–1.15, p < 0.004) fixed effects and 1.22 (95% CI: 1.04–1.44, p < 0.02) random effects. Discussion: Chronic environmental Cd exposure was associated with T2DM in a smelter community, controlling for covariates. T2DM onset <50 years was significantly associated with Cd exposure, but >50 years was not. Meta-analysis suggests that Cd exposure is associated with a small, but significant increased risk for T2DM. Available data suggest Cd exposure is associated with an increased propensity to increased insulin resistance.

A guide on meta-analysis of time-to-event outcomes using aggregate data in vascular and endovascular surgery

2020 ◽  
Vol 71 (3) ◽  
pp. 1002-1005 ◽  
Author(s):  
George A. Antoniou ◽  
Stavros A. Antoniou ◽  
Catrin Tudur Smith
Keyword(s):  
Meta Analysis ◽  
Aggregate Data ◽  
Endovascular Surgery ◽  
Time To Event
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