Dataset Information

Comparing the Overall Result and Interaction in Aggregate Data Meta-Analysis and Individual Patient Data Meta-Analysis.

ABSTRACT: The aim of the study was to examine how well aggregate data meta-analyses (ADMAs) and individual patient data meta-analyses (IPDMAs) agree in their overall results and how frequently interactions are detected in IPDMAs and ADMAs.ADMA articles immediately published before the IPDMA and matching the research topic were identified. Agreement in the overall result was achieved if the estimate was in the same direction. The number of subgroup analyses, in particular that of significant interactions, was compared between the 2 types of meta-analyses.A total of 829 IPDMA articles were identified; 129 (15.6%) were found to have a matched ADMA article and 204 paired meta-analyses were identified. Agreement in the overall effect was observed in 187 (91.7%) of the 204 paired meta-analyses. Fifty-three (26.0%) ADMAs and 121 (59.3%) IPDMAs conducted subgroup analyses and presented 150 and 634 subgroup analyses, respectively. The IPDMAs conducted 7 times more subgroup analyses on interaction (544 in IPDMAs vs 68 in ADMAs) and identified 14 times more potential interactions (44 in IPDMAs vs 3 in ADMAs).ADMAs will almost always agree with their corresponding IPDMAs in the overall result if greater efforts are made to improve the methodology in conducting ADMAs. The IPDMA is required mostly if interactions are suspected.

SUBMITTER: Huang Y

PROVIDER: S-EPMC4998822 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Comparing the Overall Result and Interaction in Aggregate Data Meta-Analysis and Individual Patient Data Meta-Analysis.

Huang Yafang Y Tang Jinling J Tam Wilson Wai-San WW Mao Chen C Yuan Jinqiu J Di Mengyang M Yang Zuyao Z

Medicine 20160401 14

The aim of the study was to examine how well aggregate data meta-analyses (ADMAs) and individual patient data meta-analyses (IPDMAs) agree in their overall results and how frequently interactions are detected in IPDMAs and ADMAs.ADMA articles immediately published before the IPDMA and matching the research topic were identified. Agreement in the overall result was achieved if the estimate was in the same direction. The number of subgroup analyses, in particular that of significant interactions, ...[more]

PMID: 27057906

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Project description:BackgroundThe 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.MethodsAccess 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.ResultsIPD 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.ConclusionsOverall, 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.

Project description:BackgroundIt remains unclear when standard systematic reviews and meta-analyses that rely on published aggregate data (AD) can provide robust clinical conclusions. We aimed to compare the results from a large cohort of systematic reviews and meta-analyses based on individual participant data (IPD) with meta-analyses of published AD, to establish when the latter are most likely to be reliable and when the IPD approach might be required.Methods and findingsWe used 18 cancer systematic reviews that included IPD meta-analyses: all of those completed and published by the Meta-analysis Group of the MRC Clinical Trials Unit from 1991 to 2010. We extracted or estimated hazard ratios (HRs) and standard errors (SEs) for survival from trial reports and compared these with IPD equivalents at both the trial and meta-analysis level. We also extracted or estimated the number of events. We used paired t tests to assess whether HRs and SEs from published AD differed on average from those from IPD. We assessed agreement, and whether this was associated with trial or meta-analysis characteristics, using the approach of Bland and Altman. The 18 systematic reviews comprised 238 unique trials or trial comparisons, including 37,082 participants. A HR and SE could be generated for 127 trials, representing 53% of the trials and approximately 79% of eligible participants. On average, trial HRs derived from published AD were slightly more in favour of the research interventions than those from IPD (HRAD to HRIPD ratio = 0.95, p = 0.007), but the limits of agreement show that for individual trials, the HRs could deviate substantially. These limits narrowed with an increasing number of participants (p < 0.001) or a greater number (p < 0.001) or proportion (p < 0.001) of events in the AD. On average, meta-analysis HRs from published AD slightly tended to favour the research interventions whether based on fixed-effect (HRAD to HRIPD ratio = 0.97, p = 0.088) or random-effects (HRAD to HRIPD ratio = 0.96, p = 0.044) models, but the limits of agreement show that for individual meta-analyses, agreement was much more variable. These limits tended to narrow with an increasing number (p = 0.077) or proportion of events (p = 0.11) in the AD. However, even when the information size of the AD was large, individual meta-analysis HRs could still differ from their IPD equivalents by a relative 10% in favour of the research intervention to 5% in favour of control. We utilised the results to construct a decision tree for assessing whether an AD meta-analysis includes sufficient information, and when estimates of effects are most likely to be reliable. A lack of power at the meta-analysis level may have prevented us identifying additional factors associated with the reliability of AD meta-analyses, and we cannot be sure that our results are generalisable to all outcomes and effect measures.ConclusionsIn this study we found that HRs from published AD were most likely to agree with those from IPD when the information size was large. Based on these findings, we provide guidance for determining systematically when standard AD meta-analysis will likely generate robust clinical conclusions, and when the IPD approach will add considerable value.

Dataset Information

Comparing the Overall Result and Interaction in Aggregate Data Meta-Analysis and Individual Patient Data Meta-Analysis.

Publications

Comparing the Overall Result and Interaction in Aggregate Data Meta-Analysis and Individual Patient Data Meta-Analysis.

Similar Datasets

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