OBJECTIVES: Network meta-analysis of randomized controlled trials (RCTs) are often based on one effect measure per study.  However, many studies have data available at multiple time points. Furthermore, not all studies might have measured the outcomes at the same time points. As an alternative to network meta-analysis based on the results at one time point, a network meta-analysis method is presented that allows for the simultaneous analysis of outcomes at multiple time points. METHODS: The development of outcomes over time of interventions compared in a RCT are modeled with fractional polynomials, and the difference between the parameters of these polynomials within a trial are synthesized across studies with a Bayesian network meta-analysis. RESULTS: The proposed models are illustrated with an analysis of RCTs evaluating interventions for osteoarthritis of the knee. Fixed and random effects first and second order fractional polynomials were evaluated. CONCLUSIONS: Network meta-analysis with models where the treatment effect is represented with several parameters using fractional polynomials can be used to simultaneously analyze results at multiple follow-up times that are not consistent across studies.