Network meta-analyses (NMA) of survival data often rely on the proportional hazards (PH) assumption, however, this assumption fails when survival curves intersect. With the emergence of innovative therapies such as immunotherapy, the importance of NMA based on non-proportional hazards (non-PH) in the current evidence-based medicine evaluation of oncology drugs has become increasingly prominent. Fractional polynomial (FP) models do not rely on the assumption of PH, which can flexibly capture the characteristics of survival curves, and the corresponding fitting effects are better than those of the PH models. This study introduced a complete workflow in R for NMA using FP models with non-PH.