With the continuous progress of national medical insurance strategic purchasing and value-based healthcare, pharmacoeconomic evaluation, serving as a technical tool for assessing the cost-effectiveness of healthcare interventions, has played an important role in policy decision support. Comparative efficacy evidence is the core data source for pharmacoeconomic evaluation, and also the foundation for conducting pharmacoeconomic research. In recent years, the number of innovative drugs approved based on single-arm trial has been increasing. Most existing randomized controlled clinical trials are also placebo-controlled or compared with traditional treatments, unable to directly meet the need for efficacy evidence of comparisons with conventional or standard treatments in pharmacoeconomic evaluations. In the absence of direct comparative efficacy evidence, exploring indirect comparison methods for efficacy has become a cutting-edge direction in pharmacoeconomic evaluation. Through a comprehensive literature review and systematic analysis, this study focuses on five indirect comparison methods based on individual patient data for population adjustment, including match adjusted indirect comparison (MAIC), simulated treatment comparison (STC), propensity score matching (PSM), inverse probability of treatment weighting (IPTW) and network meta regression (NMR), and discussing their basic concepts, advantages and disadvantages and application comparisons. Finally, it provides methodological suggestions on how to choose an indirect comparison method for efficacy, with the aim of promoting the generation of higher-quality indirect comparison evidence for efficacy and advancing pharmacoeconomic evaluation to provide high-quality evidence references for healthcare policy decision-making.