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Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?

ABSTRACT: One of the biggest challenges for network meta-analysis is inconsistency, which occurs when the direct and indirect evidence conflict. Inconsistency causes problems for the estimation and interpretation of treatment effects and treatment contrasts. Krahn and colleagues proposed the net heat approach as a graphical tool for identifying and locating inconsistency within a network of randomized controlled trials. For networks with a treatment loop, the net heat plot displays statistics calculated by temporarily removing each design one at a time, in turn, and assessing the contribution of each remaining design to the inconsistency. The net heat plot takes the form of a matrix which is displayed graphically with coloring indicating the degree of inconsistency in the network. Applied to a network of individual participant data assessing overall survival in 7531 patients with lung cancer, we were surprised to find no evidence of important inconsistency from the net heat approach; this contradicted other approaches for assessing inconsistency such as the Bucher approach, Cochran's Q statistic, node-splitting, and the inconsistency parameter approach, which all suggested evidence of inconsistency within the network at the 5% level. Further theoretical work shows that the calculations underlying the net heat plot constitute an arbitrary weighting of the direct and indirect evidence which may be misleading. We illustrate this further using a simulation study and a network meta-analysis of 10 treatments for diabetes. We conclude that the net heat plot does not reliably signal inconsistency or identify designs that cause inconsistency.

SUBMITTER: Freeman SC

PROVIDER: S-EPMC6899484 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND: Integrating gene expression profiles and metabolic pathways under different experimental conditions is essential for understanding the coherence of these two layers of cellular organization. The network character of metabolic systems can be instrumental in developing concepts of agreement between expression data and pathways. A network-driven interpretation of gene expression data has the potential of suggesting novel classifiers for pathological cellular states and of contributing to a general theoretical understanding of gene regulation. RESULTS: Here, we analyze the coherence of gene expression patterns and a reconstruction of human metabolism, using consistency scores obtained from network and constraint-based analysis methods. We find a surprisingly strong correlation between the two measures, demonstrating that a substantial part of inconsistencies between metabolic processes and gene expression can be understood from a network perspective alone. Prompted by this finding, we investigate the topological context of the individual biochemical reactions responsible for the observed inconsistencies. On this basis, we are able to separate the differential contributions that bear physiological information about the system, from the unspecific contributions that unravel gaps in the metabolic reconstruction. We demonstrate the biological potential of our network-driven approach by analyzing transcriptome profiles of aldosterone producing adenomas that have been obtained from a cohort of Primary Aldosteronism patients. We unravel systematics in the data that could not have been resolved by conventional microarray data analysis. In particular, we discover two distinct metabolic states in the adenoma expression patterns. CONCLUSIONS: The methodology presented here can help understand metabolic inconsistencies from a network perspective. It thus serves as a mediator between the topology of metabolic systems and their dynamical function. Finally, we demonstrate how physiologically relevant insights into the structure and dynamics of metabolic networks can be obtained using this novel approach.

Project description:Objective: We conducted a network meta-analysis to comprehensively compare various anticancer agents used in transarterial chemoembolization (TACE) based on the Bayesian theorem. Methods: Globally recognized electronic databases, including PubMed, EMBASE, and Cochrane Central, were searched to retrieve relevant randomized controlled trials (RCTs) comparing anticancer agents in TACE for hepatocellular carcinoma (HCC) patients. The therapeutic response, adverse events and overall survival rate were selected as parametric data to evaluate the clinical efficacy. Quantitative network meta-analysis and pair-wise analysis were conducted to compare the relative parameters. Results: Of the 4242 retrieved articles, 17 RCTs containing 2330 patients fulfilled the inclusion criteria. The network meta-analysis exhibited that the application of anthracycline and mitomycin plus pyrimidine presented the best clinical values regarding all parametric data (probability P=0.45, 0.32 and 0.35 regarding comparison of response rate, adverse event and overall survival, respectively). Accordingly, further investigation on specific anticancer agents indicated that the combination of doxorubicin and mitomycin plus gemcitabine was the best agent combination in TACE (probability P=0.49, 0.37 and 0.77 regarding comparison of response rate, adverse event and overall survival, respectively). Moreover, an additional study indicated that the single use of an anticancer agent prior to embolism brought no benefit compared with bland embolism without any agent (Test Z=0.15, 0.84, 1.22 and P=0.88, 0.40, 0.22 regarding comparison of response rate, adverse event and overall survival, respectively). However, the combined use of anticancer agents in TACE showed significantly better clinical efficacy than single use (Test Z=4.40, 3.94, 0.24 and P<0.001, <0.001, =0.81 regarding comparison of response rate, adverse event and overall survival, respectively); thus, combination utilization was recommended. Conclusions: The combined use of anticancer agents in TACE was recommended. Application of anthracycline and mitomycin plus pyrimidine seemed to be the best choice for clinical consideration. Additionally, the combination of doxorubicin and mitomycin plus gemcitabine may be the best specific anticancer agent combination in TACE currently, although additional RCTs are expected to support our conclusion.

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Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?

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