Evidence map›Paper›PMID 39222272›Full record

ArticlePharmacoEconomics2024

Effects and Costs of Hepatitis C Virus Elimination for the Whole Population in China: A Modelling Study.

Meiyu Wu, Jing Ma, Sini Li, Shuxia Qin, Chongqing Tan, Ouyang Xie, Andong Li, Aaron G Lim, Xiaomin Wan

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In one paragraph

Article in PharmacoEconomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

9 authors.

Meiyu WuDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Rd, Changsha, 410011, Hunan, China.
Jing MaDepartment of Gastroenterology, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China.
Sini LiThe Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Shuxia QinDepartment of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China.
Chongqing TanDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Rd, Changsha, 410011, Hunan, China.
Ouyang XieDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Rd, Changsha, 410011, Hunan, China.
Andong LiDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Rd, Changsha, 410011, Hunan, China.
Aaron G LimBristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK. aaron.lim@bristol.ac.uk.
Xiaomin WanDepartment of Pharmacy, The Second Xiangya Hospital, Central South University, 139 Renmin Rd, Changsha, 410011, Hunan, China. wanxiaomin@csu.edu.cn.ORCID 0000-0001-5315-8141

Funding

Fundamental Research Funds for Central Universities of the Central South University 2023ZZTS0924National Natural Science Foundation of China 71874209Natural Science Foundation of Hunan Province 2023JJ60503research project of the Health Commission of Hunan province 202113050283
6 · The paper itself

Abstract

BACKGROUND AND

objectiveChina has the highest number of hepatitis C virus (HCV) infections in the world. However, it is unclear what levels of screening and treatment are needed to achieve the WHO 2030 hepatitis C elimination targets. We aimed to evaluate the impact of scaling up interventions on the hepatitis C epidemic and determine how and at what cost these elimination targets could be achieved for the whole population in China.

methodsWe developed a compartmental model incorporating HCV transmission, disease progression, and care cascade for the whole population in China, calibrated with data on demographics, injecting drug use, HCV prevalence, and treatments. Five different scenarios were evaluated for effects and costs for 2022-2030. All costs were converted to 2021 US dollar (USD) and discounted at an annual rate of 5%. One-way sensitivity analyses were conducted to assess the robustness of the model.

resultsUnder the status quo scenario, the incidence of hepatitis C is projected to increase from 60.39 (57.60-63.45) per 100,000 person-years in 2022 to 68.72 (65.3-73.97) per 100,000 person-years in 2030, and 2.52 million (1.94-3.07 million) infected patients are projected to die between 2022 and 2030, of which 0.76 (0.61-1.08) million will die due to hepatitis C. By increasing primary screening to 10%, conducting regular rescreening (annually for PWID and every 5 years for the general population) and treating 90% of patients diagnosed, the incidence would be reduced by 88.15% (86.61-89.45%) and hepatitis C-related mortality by 60.5% (52.62-65.54%) by 2030, compared with 2015 levels. This strategy would cost USD 52.78 (USD 43.93-58.53) billion.

conclusionsWithout changes in HCV prevention and control policy, the disease burden of HCV in China will increase dramatically. To achieve the hepatitis C elimination targets, China needs to sufficiently scale up screening and treatment.

Indexed as

Hepatitis CAdolescentAdultAgedAntiviral AgentsChinaDisease EradicationDisease ProgressionFemaleHealth Care CostsHumansIncidenceMaleMass ScreeningMiddle AgedModels, EconomicAntiviral Agents

Identifiers

PMID39222272

What OpenQuestion holds

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Registered trials

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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.