When we shouldn't borrow information from an existing network of trials for planning a new trial.

To achieve higher power or increased precision for a new trial, methods based on updating network meta-analysis (NMA) have been proposed by researchers. However, this approach could potentially lead to misinterpreted results and misstated conclusions. This work aims to investigate the potential inflation of type I error risk when a new trial is conducted only when, based on a -value of the comparison in the existing network, a "promising" difference between two treatments is noticed. We use simulations to evaluate the scenarios of interest. In particular, a new trial is to be conducted independently or depending on the results from previous NMA in various scenarios. Three analysis methods are applied to each simulation scenario: with the existing network, sequential analysis and without the existing network. For the scenario that the new trial will be conducted only when a promising finding (-value ) is indicated by the existing network, the type I error risk increased dramatically (38.5% in our example data) when analyzed with the existing network and sequential analysis. The type I error is controlled at 5% when analyzing the new trial without the existing network. If the intention is to combine a trial result with an existing network of evidence, or if it is expected that the trial will eventually be included in a network meta-analysis, then the decision that a new trial is performed should not depend on a statistically "promising" finding indicated by the existing network.