Findings and interpretations
This study included 21 IPD-NMAs published between 2007 and 2019, identified from a comprehensive literature search. We investigated the statistical analysis methods used and assessed the reporting quality based on PRISMA-IPD and PRISMA-NMA checklists and methodological quality using the AMSTAR-2 tool. Overall, the reporting of statistical analysis methods was suboptimal, and the reporting quality and methodological quality were low. Compliance rates were insufficient for most of the items of PRISMA-IPD, PRISMA-NMA, and AMSTAR-2.
Of the 21 IPD-NMAs, 10 combined both individual participant data and aggregate data, because IPD were not available from some relevant trials. We also found that the Bayesian IPD-NMAs were more likely to use the 1-stage process, and the Frequentist IPD-NMAs were more likely to use the 2-stage process. Reluctance to share data is a major obstacle to obtaining IPD and performing IPD meta-analysis [
36,
37]. A previous study showed that IPD sharing may depend on study characteristics, including funding type, study size, study risk of bias, and treatment effect [
27]. Of the 21 included IPD-NMAs, only three mentioned the retrieval bias and none assessed the impact of the retrieval bias. One of the advantages of IPD meta-analyses is that it allows the application of appropriate multiple imputation techniques to solve problems related to missing data [
3]. However, only 23.8% of the IPD-NMAs reported the use of statistical techniques to handle missing participant data. Meta-analyses often have intrinsic heterogeneity, which can affect the reliability and validity of results [
38]. Heterogeneity was assessed in 71.4% of the IPD-NMAs, and the sources of heterogeneity were mostly explored by performing the subgroup analysis, meta-regression analysis, or sensitivity analysis. The consistency assumption is imperative for a valid NMA, and the assessment of inconsistency should be fully reported in NMAs [
24,
33]. However, no more than 45.0% of the IPD-NMAs used specific methods to evaluate consistency. The transitivity assumption is another important aspect in NMAs [
39], but none of the included IPD-NMAs assessed the transitivity, which should be given more attention in the future work.
For reporting quality based on 31 PRISMA-IPD items and 5 PRISMA-NMA supplemental items, compliance rates were above 70.0% for nine items, lower than 40.0% for 14 items, and lower than 15.0% for 6 items. For IPD meta-analyses, the importance of checking and correcting any inaccuracies or errors in the IPD is self-evident [
1]. However, more than 60.0% of IPD-NMAs did not explore data integrity and about 85.7% of IPD-NMAs did not report data integrity. Therefore, future IPD-NMAs should clarify which aspects of IPD were subject to data checking, how data checking was done, and report any important issues identified in checking IPD. IPD meta-analyses are particularly useful for exploring the participant-level variation of treatment response [
1,
40]. Only about half of the included IPD-NMAs described methods for exploring variation in effects by the study- or participant-level characteristics and stated participant-level characteristics that were analyzed as potential effect modifiers. About 86.0% of IPD-NMAs did not present the network of geometry nor did they summarize the network geometry, which affected the understanding of NMAs [
24,
41]. Furthermore, deficiencies were also identified in items related to protocol and registration, search, study selection, data collection process, risk of bias in individual studies, results of syntheses, risk of bias across studies, and funding.
Of the 16 individual AMSTAR-2 items, only four items obtained compliance rates higher than 50.0%, and seven obtained compliance rates lower than 20.0%. Only 4.8% of the IPD-NMAs explained their selection of the study designs for inclusion in the review, 19.0% provided a list of excluded studies and justified the exclusions, and none of the IPD-NMAs reported sources of funding for the studies included in the review, which is similar to the findings of other types of SRs and meta-analyses [
38,
42,
43]. Therefore, these may be some common methodological shortcomings of any types of SRs. In SRs, assessing the risk of bias of primary studies and investigating publication bias are of great importance as these will gauge the validity of meta-analytic results, affect the interpretation of results, and limit our ability to draw conclusions [
43,
44]. Unfortunately, only 28.6% of IPD-NMAs used a satisfactory technique for assessing the RoB in individual studies included, and only 19% of IPD-NMAs assessed the potential impact of RoB on the results of the meta-analyses. In addition, only 14.3% of the included IPD-NMAs investigated the publication bias and discussed its likely impact on the results of the review. Approximately 30.0% of the IPD-NMAs were industry-sponsored, and no more than 40.0% of IPD-NMAs reported potential conflicts of interest and funding sources, which may lead to potential risks of funding bias [
21]. Publishing protocols can reduce the risk of researcher bias and outcome reporting bias [
45‐
47]. Empirical studies have also found that a priori protocol can improve the methodological quality of SR [
34,
48]. Our study showed that IPD-NMAs with a priori protocol tended to have higher methodological quality than IPD-NMAs without a priori protocol, although the difference was not statistically significant.
Comparison of our findings with other studies
A previous study found that key methodological and reporting issues such as consistency assumption, study protocol, and statistical approaches for missing participant data were often insufficiently reported in IPD indirect comparison studies [
3]. These results were similar to the findings of our analyses of IPD-NMAs. According to our knowledge, two previous studies [
21,
23] explored the statistical methods, methodological and reporting characteristics of aggregate data NMAs. These two empirical studies found that, of the included NMAs, only 53.0% assessed inconsistency, 56.0% explored heterogeneity, and less than 40.0% investigated publication bias, which are also similar to the results of our study. This suggested that IPD-NMAs and aggregate data NMAs may have the same defects. Compared with Cochrane NMAs [
24], IPD-NMAs had significantly lower compliance rates in 12 AMSTAR-2 items and 13 PRISMA-NMA items, revealing that both the methodological and reporting quality of IPD-NMAs were lower than Cochrane NMAs. Therefore, there was room for further improvement in both Cochrane NMAs and IPD-NMAs, such as the geometry of the network, the risk of bias in individual studies, and the assessment of inconsistency.
Strengths and limitations
This is the first comprehensive evaluation of published IPD-NMAs, in terms of statistical methods used, reporting quality based on PRISMA-IPD and PRISMA-NMA checklists, and methodological quality based on the AMSTAR-2 tool. Furthermore, we also conducted stratified analyses to explore potential factors that may affect the reporting and methodological quality and further performed the correlation analysis to evaluate whether the reporting quality was relevant to the methodological quality. However, our study also has some limitations. First, the number of IPD-NMAs included in our study was small, although we have identified all available IPD-NMAs by conducting a comprehensive literature search. Second, our data depended on the information reported in the included IPD-NMAs, so we could not rule out the possibility that some important methods were appropriately used in the study but not reported [
3]. Third, we mainly focused on the impact of selected factors on the methodological and reporting quality of IPD-NMAs. Finally, we included a very small number of IPD-NMAs and conducted a large number of statistical tests. Any significant results of stratified analyses should be interpreted with caution.