Evidence map›Paper›PMID 39316305›Full record

ArticleInternational journal of clinical pharmacy2024

Assessing the cost-effectiveness of replacing antimetabolites with mTOR inhibitors in heart transplant immunosuppression in China: a network meta-analysis-based economic evaluation.

Yajie Gu, Bing Liu, Xiaonan Lin, Jinjin Chen, Xin Chen, Yingshuo Jiang, Yifan Zhu, Xin Li, Sheng Lou, Junrong Zhu

Abstract readNetwork Meta-Analysis
PubMed Publisher
In one paragraph

Article in International journal of clinical pharmacy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

10 authors.

Yajie Gu *Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Bing Liu *Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Xiaonan LinDepartment of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Jinjin ChenDepartment of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Xin ChenDepartment of Cardiothoracic Surgery, Nanjing First Hospital, Nanjing Hospital Affiliated to Nanjing Medical University, Nanjing, 210006, China.
Yingshuo JiangDepartment of Cardiothoracic Surgery, Nanjing First Hospital, Nanjing Hospital Affiliated to Nanjing Medical University, Nanjing, 210006, China.
Yifan ZhuDepartment of Cardiothoracic Surgery, Nanjing First Hospital, Nanjing Hospital Affiliated to Nanjing Medical University, Nanjing, 210006, China.
Xin LiSchool of Pharmacy, Nanjing Medical University, Nanjing, 211166, China.
Sheng LouDepartment of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Junrong ZhuDepartment of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China. jrzhu@cpu.edu.cn.ORCID http://orcid.org/0009-0007-2585-5602

Funding

Nanjing Pharmaceutical Society - Changzhousiyao Hospital Pharmaceutical Research Fund 2023YX001
6 · The paper itself

Abstract

backgroundAlthough several pharmacoeconomic studies have assessed the cost-effectiveness of maintenance immunosuppressive regimens for heart transplant recipients, economic comparisons between various combination drug therapies remain sparse.

aimThis study used an economic evaluation based on network meta-analysis to assess the cost-effectiveness of four immunosuppressive regimens for adult heart transplant recipients in China.

methodWe conducted a systematic search for clinical trials in PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, and VIP database. A validated Markov model was adapted to reflect the Chinese medical landscape. Four maintenance immunosuppression regimens were considered: tacrolimus/mycophenolate mofetil (TAC/MMF), cyclosporine/mycophenolate mofetil (CSA/MMF), everolimus/cyclosporine (EVL/CSA), and sirolimus/tacrolimus (SRL/TAC). The probabilities of health events were derived from a comprehensive literature review. Direct medical costs, adjusted for 2022 values, were from public documents and websites, while utilities for quality-adjusted life-years (QALYs) were taken from previous studies. Primary outcomes were mean lifetime cost, QALYs, and cost-effectiveness, with a willingness-to-pay (WTP) threshold set at three times China's GDP per capita in 2022. Sensitivity analyses were conducted to test the robustness of the results.

resultsThe base case analysis identified TAC/MMF as the most cost-effective regimen, producing a mean of 6.31 QALYs per patient at a cost of Chinese Yuan (CNY) 534,182.89. Sensitivity analyses consistently reinforced TAC/MMF as the most cost-effective and robust choice.

conclusionTAC/MMF is the most cost-effective maintenance immunosuppressive regimen for heart transplant recipients within the Chinese health system. The study findings are reinforced by sensitivity analyses, affirming their robustness amid various uncertainties.

Indexed as

Cost-Effectiveness AnalysisHeart TransplantationImmunosuppressive AgentsMTOR InhibitorsChinaCyclosporineDrug Therapy, CombinationEverolimusHumansMycophenolic AcidQuality-Adjusted Life YearsSirolimusTacrolimusCyclosporineEverolimusImmunosuppressive AgentsMTOR InhibitorsMycophenolic AcidSirolimusTacrolimusCost-effectivenessHeart transplantationImmunosuppressionLong-term simulationMarkov model

Identifiers

PMID39316305

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.