Abstract
Meta-analysis is important in oncological research to provide a more reliable answer to a clinical research question that was assessed in multiple studies but with inconsistent results. Pair-wise meta-analysis can be applied when comparing two treatments at once, whereas it is possible to compare multiple treatments at once with network meta-analysis (NMA). After careful systematic review of the literature and quality assessment of the identified studies, there are several assumptions in the use of meta-analysis. First, the added value of meta-analysis should be evaluated by examining the comparability of study populations. Second, the appropriate comparator in meta-analysis should be chosen according to the types of comparisons made in individual studies: (1) Experimental and comparator arms are different treatments (A vs. B); (2) Substitution of a conventional treatment by an experimental treatment (A+B vs. A+C); or (3) Addition of an experimental treatment (A+B vs. B). Ideally there is one common comparator treatment, but when there are multiple common comparators, the most efficacious comparator is preferable. Third, treatments can only be adequately pooled in meta-analysis or merged into one treatment node in NMA when considering likewise mechanism of action and similar setting in which treatment is indicated. Fourth, for both pair-wise meta-analysis and NMA, adequate assessment of heterogeneity should be performed and sub-analysis and sensitivity analysis can be applied to objectify a possible confounding factor. Network inconsistency, as statistical manifestation of violating the transitivity assumption, can best be evaluated by node-split modeling. NMA has advantages over pair-wise meta-analysis, such as clarification of inconsistent outcomes from multiple studies including multiple common comparators and indirect effect calculation of missing direct comparisons between important treatments. Also, NMA can provide increased statistical power and cross-validation of the observed treatment effect of weak connections with reasonable network connectivity and sufficient sample-sizes. However, inappropriate use of NMA can cause misleading results, and may emerge when there is low network connectivity, and therefore low statistical power. Furthermore, indirect evidence is still observational and should be interpreted with caution. NMA should therefore preferably be conducted and interpreted by both expert clinicians in the field and an experienced statistician. Finally, the use of meta-analysis can be extended to other areas, for example the identification of prognostic and predictive factors. Also, the integration of evidence from both meta-analysis and expert opinion can improve the construction of prognostic models in real-world databases.
Highlights
IN THE USE OF META-ANALYSIS IN ONCOLOGY properly in the field of oncology, with studies from upper gastrointestinal cancer as an example.In the past decade, the number of pair-wise and network meta-analyses published increased rapidly in the research field of oncology
In the network meta-analyses (NMA) comparing all first-line chemotherapy regimens for advanced esophagogastric cancer, 5-FU, S-1, and capecitabine were merged to the class of fluoropyrimidines to increase statistical power and overcome network disconnection, but only after it was ensured that these were similar in terms of efficacy [58]
In a published pair-wise meta-analysis comparing S-1 combination therapy vs. S-1 alone, sub-group analysis showed that the heterogeneity in the main analysis could be clarified by the fact that three smaller studies from China tended to overestimate the effect of S-1 combination therapy, whereas the studies conducted in Japan did not [70]
Summary
IN THE USE OF META-ANALYSIS IN ONCOLOGY properly in the field of oncology, with studies from upper gastrointestinal cancer as an example. A recent study showed that there were more than 100 network meta-analyses (NMA) in oncology published between 2006 and 2015, mostly on upper gastrointestinal oncology, such as esophagogastric cancer and pancreatic cancer [1]. In meta-analysis, the data of multiple studies, preferable randomized controlled trials (RCTs), that address a similar research question are pooled together. The primary aim of metaanalysis is not to create new evidence, but to establish a definitive answer to a clinical research question such as “Is treatment A more effective than B?” that was assessed in multiple studies but with inconsistent results [3, 4]. We will review the most important points to decide whether the use of meta-analysis is appropriate and how to conduct meta-analysis
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