Evidence map›Paper›PMID 40432721›Full record

ArticleFrontiers in medicine2025

Cost-effectiveness analysis of ambroxol for the treatment of Chinese patients with Gaucher disease.

Yueyang Huang, Hongmei Yuan, Zhe Huang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yueyang HuangSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.
Hongmei YuanSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.
Zhe HuangSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gaucher disease (GD) is an autosomal recessive disorder with a wide range of clinical symptoms that cause abnormal function of parenchymal organs such as liver and spleen in patients. Enzyme replacement therapy, represented by imiglucerase, is a common approach for GD treatment. However, limited efficacy and high cost are important factors restricting its use. Ambroxol has gradually attracted attention due to its ease of administration, safety, and efficacy. However, there is no pharmacoeconomic evaluation of ambroxol for the treatment of GD in China. The cost-effectiveness profile of ambroxol combined with imiglucerase therapy for the treatment of GD, as opposed to imiglucerase monotherapy, needs to be investigated. Objective: This study aimed to analyze the cost-effectiveness of ambroxol for GD in China from the perspective of the Chinese healthcare system. Methods: We constructed an eight-state Markov model based on the disease characteristics of GD. The Markov cycle was 1 month. The time horizon was 6 years. The willingness-to-pay threshold was chosen to be 1-3 times the gross national product (GDP) per capita. The incremental cost-effectiveness ratio (ICER) was calculated from the base-case analysis, and one-way sensitivity analyses and probabilistic sensitivity analyses were performed. Results: The ICER value was ¥223,726.70, which was between 1 and 3 times GDP per capita. Sensitivity analysis showed that the cost of imiglucerase had a significant effect on ICER as well as demonstrating the stability of the results. Conclusion: Ambroxol combination therapy is a cost-effective regimen compared with imiglucerase monotherapy.

Indexed as

ambroxolcost-effectivenessGaucher diseaseimigluceraseincremental cost-effectiveness ratioMarkov modelsensitivity analysis

Identifiers

PMID40432721
PMCPMC12106307

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.