ArticlePloS one2023
Economic evaluation of prenatal screening for fetal aneuploidies in Thailand.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prenatal Screening for Common Aneuploidy in Southeast Asian Countries: A Systematic Review of Challenges and Opportunities.Prenatal diagnosis · 2026Pooled it
- Effects of an animated educational video on knowledge of cell-free DNA screening among Thai pregnant women: a randomized control trial.BMC pregnancy and childbirth · 2023Trial
- Cost-effectiveness of non-invasive prenatal testing (NIPT) versus direct amniocentesis for screening of fetal chromosomal aneuploidies in Brazilian private health system.Cost effectiveness and resource allocation : C/E · 2026Review
- Effectiveness of Fetal Medicine Foundation's Non-Biochemical Risk Calculation Algorithm in Detection of Common Trisomies Screening at 11-13 weeks of Gestation: 12 Years' Experience in Northern Thailand.International journal of women's health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Historically, there has been a lack of cost-effectiveness data regarding the inclusion of universal non-invasive prenatal testing (NIPT) for trisomy 21, 18, and 13 in the benefit package of the Universal Health Coverage (UHC) in Thailand. Therefore, this study aimed to perform the cost-benefit analysis of prenatal screening tests and calculate the budget impact that would result from the implementation of a universal NIPT program. A decision-tree model was employed to evaluate cost and benefit of different prenatal chromosomal abnormalities screenings: 1) first-trimester screening (FTS), 2) NIPT, and 3) definitive diagnostic (amniocentesis). The comparison was made between these screenings and no screening in three groups of pregnant women: all ages, < 35 years, and ≥ 35 years. The analysis was conducted from societal and governmental perspectives. The costs comprised direct medical, direct non-medical, and indirect costs, while the benefit was cost-avoidance associated with caring for children with trisomy and the loss of productivity for caregivers. Parameter uncertainties were evaluated through one-way and probabilistic sensitivity analyses. From a governmental perspective, all three methods were found to be cost-beneficial. Among them, FTS was identified as the most cost-beneficial, especially for pregnant women aged ≥ 35 years. From a societal perspective, the definitive diagnostic test was not cost-effective, but the other two screening tests were. The most sensitive parameters for FTS and NIPT strategies were the productivity loss of caregivers and the incidence of trisomy 21. Our study suggested that NIPT was the most cost-effective strategy in Thailand, if the cost was reduced to 47 USD. This evidence-based information can serve as a crucial resource for policymakers when making informed decisions regarding the allocation of resources for prenatal care in Thailand and similar context.
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Registered trials
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.