Entropy coding, which acts as one of the most important compression tools in video coding standard, had been improved step by step for HEVC. There are also several advanced methods which provide better performance than current solutions of HEVC proposed during the standardization of HEVC. However, these methods are all tested in different conditions. Comprehensive evaluation of these advanced methods under a common scenario is desired to indicate where the potential improvement of entropy coding may come from for next generation video codec. In this paper, we first introduce several advanced entropy coding methods for DCT transform coefficients, which aim to improve CABAC performance from two aspects - context modeling and probability updating. Then some modifications based on these original ones are presented. Comprehensive comparison of these methods is conducted under common test conditions. Besides, some combined methods of these two aspects are also tested. Experimental results show that all individual approaches can achieve coding gain and two new combined methods can reduce the BD-Rate up to 1.7%, 1.2% and 1.0% on common test sequences and 1.4%, 1.0% and 1.1% on 4K sequences under all intra, random access and low delay configurations, respectively.