Evidence mapPaperPMID 39327612Full record

SynthesisGlobal health research and policy2024

Synthesized economic evidence on the cost-effectiveness of screening familial hypercholesterolemia.

Mengying Wang, Shan Jiang, Boyang Li, Bonny Parkinson, Jiao Lu, Kai Tan, Yuanyuan Gu, Shunping Li

Abstract readSystematic Review
In one paragraph

Synthesis in Global health research and policy, 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. Review
  2. Article
  3. 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

8 authors.

Mengying WangSchool of Management, Shanxi Medical University, Taiyuan, Shanxi, China.
Shan JiangMacquarie Business School and Australian Institute of Health Innovation, Macquarie University Centre for the Health Economy, Macquarie University, Level 5, 75 Talavera Road, Macquarie Park, Sydney, NSW, 2109, Australia. shan.jiang@mq.edu.au.ORCID http://orcid.org/0000-0003-1015-1278
Boyang LiSchool of Political Science and Public Administration, Wuhan University, Wuhan, Hubei, China.
Bonny ParkinsonMacquarie Business School and Australian Institute of Health Innovation, Macquarie University Centre for the Health Economy, Macquarie University, Level 5, 75 Talavera Road, Macquarie Park, Sydney, NSW, 2109, Australia.
Jiao LuSchool of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Kai TanSchool of Management, Shanxi Medical University, Taiyuan, Shanxi, China.
Yuanyuan GuMacquarie Business School and Australian Institute of Health Innovation, Macquarie University Centre for the Health Economy, Macquarie University, Level 5, 75 Talavera Road, Macquarie Park, Sydney, NSW, 2109, Australia.
Shunping LiCentre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China. lishunping@sdu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFamilial hypercholesterolemia (FH) is a prevalent genetic disorder with global implications for severe cardiovascular diseases. Motivated by the growing recognition of the need for early diagnosis and treatment of FH to mitigate its severe consequences, alongside the gaps in understanding the economic implications and equity impacts of FH screening, this study aims to synthesize the economic evidence on the cost-effectiveness of FH screening and to analyze the impact of FH screening on health inequality.

methodsWe conducted a systematic review on the economic evaluations of FH screening and extracted information from the included studies using a pre-determined form for evidence synthesis. We synthesized the cost-effectiveness components involving the calculation of synthesized incremental cost-effectiveness ratios (ICERs) and net health benefit (NHB) of different FH screening strategies. Additionally, we applied an aggregate distributional cost-effectiveness analysis (DCEA) to assess the impact of FH screening on health inequality.

resultsAmong the 19 studies included, over half utilized Markov models, and 84% concluded that FH screening was potentially cost-effective. Based on the synthesized evidence, cascade screening was likely to be cost-effective, with an ICER of $49,630 per quality-adjusted life year (QALY). The ICER for universal screening was $20,860 per QALY as per evidence synthesis. The aggregate DCEA for six eligible studies presented that the incremental equally distributed equivalent health (EDEH) exceeded the NHB. The difference between EDEH and NHB across the six studies were 325, 137, 556, 36, 50, and 31 QALYs, respectively, with an average positive difference of 189 QALYs.

conclusionsOur research offered valuable insights into the economic evaluations of FH screening strategies, highlighting significant heterogeneity in methods and outcomes across different contexts. Most studies indicated that FH screening is cost-effective and contributes to improving overall population health while potentially reducing health inequality. These findings offer implications that policies should promote the implementation of FH screening programs, particularly among younger population. Optimizing screening strategies based on economic evidence can help identify the most effective measures for improving health outcomes and maximizing cost-effectiveness.

Indexed as

Cost-Benefit AnalysisHyperlipoproteinemia Type IIMass ScreeningHumansQuality-Adjusted Life YearsCost-effectivenessEquityFamilial hypercholesterolemiaHealth economicsScreeningSystematic review

Identifiers

PMID39327612
PMCPMC11425997

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.