Deriving Health Utility Values Using Mapping Methods Among the Chinese Population: A Systematic Review.

Abstract

Objectives: Despite an increasing number of mapping studies being conducted in China, there is an absence of a systematic reviews, which makes it difficult to inform the applications and further assess the methodological consistency, accuracy, and applicability of existing mapping studies. The objective of this review is to consolidate existing evidence, identify methodological gaps, and provide recommendations for improving mapping studies conducted among the Chinese population.

Methods: A systematic literature search was conducted in 14 databases from inception to May 31, 2025 to identify studies that developed mapping algorithms to estimate health utility values, specifically among Chinese populations. A data template was applied to extract dataset information, source and target measures, mapping types (direct vs indirect), models used, goodness-of-fit indicators, validation methods, and the optimal mapping algorithms selected. Potential challenges for future related studies were further discussed.

Results: A total of 33 studies was included. Most studies (87.9%) focused on mapping disease-specific non-preference-based measures (PBMs) to generic PBMs. The studies covered a broad range of disease areas, including oncology (36.4%), musculoskeletal disorders (15.2%), metabolic diseases (15.2%), cardiovascular diseases (9.1%), and neurological conditions (6.1%). All studies used direct mapping, with the ordinary least squares model (n = 37) being used most frequently, followed by Tobit model (n = 32) and Beta model (n = 22). Eleven studies explored indirect mapping, with the Ordered Logit and Ordered Probit models being the most employed techniques. Thirty-two studies conducted internal validation, with the N-fold cross-validation being the most used method-no study conducted external validation. The sample size ranged from 133 to 3320, with a median sample size of 553. Conducted conceptual analysis was performed in 81.8% of the studies to assess the degree of overlap between the source measure and target measure; 72.7% of the studies reported the utility/score distributions, and 15.2% of studies further reported the response distributions.

Conclusion: This systematic review provides insights into methodologies employed in mapping studies in China and identifies key areas for improvement. Addressing issues related to sample size, conceptual overlap, model selection, and validation methods will enhance the quality and applicability of mapping algorithms, ultimately supporting more robust cost-utility analyses in the Chinese healthcare system.