ArticleJournal of personalized medicine2022
Cost-Effectiveness of Screening Algorithms for Familial Hypercholesterolaemia in Primary Care.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Cost-Effectiveness of Screening Strategies for Familial Hypercholesterolaemia: An Updated Systematic Review.PharmacoEconomics · 2024Pooled it
- Improving the clinical diagnosis of familial hypercholesterolemia among patients attending diabetes and cardiology clinics.American journal of preventive cardiology · 2026Article
- Unveiling Familial Hypercholesterolemia-Review, Cardiovascular Complications, Lipid-Lowering Treatment and Its Efficacy.International journal of molecular sciences · 2024Review
- Reducing Premature Coronary Artery Disease in Malaysia by Early Identification of Familial Hypercholesterolemia Using the Familial Hypercholesterolemia Case Ascertainment Tool (FAMCAT): Protocol for a Mixed Methods Evaluation Study.JMIR research protocols · 2023Article
- A comparison of the Netherlands, Norway and UK familial hypercholesterolemia screening programmes with implications for target setting and the UK's NHS long term plan.PLOS global public health · 2023Article
- Familial Hypercholesterolemia and Its Current Diagnostics and Treatment Possibilities: A Literature Analysis.Medicina (Kaunas, Lithuania) · 2022Review
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 at 3 institutions in 2 countries.
Funding
Abstract
Although familial hypercholesterolemia (FH) screening within primary care is considered cost-effective, which screening approach is cost-effective has not been established. This study determines the cost-effectiveness of six case-finding strategies for screening of electronic health records to identify index patients who have genetically confirmed monogenic FH in English primary care. A decision tree was constructed to represent pathways of care for each approach (FH Case Identification Tool (FAMCAT) versions 1 and 2, cholesterol screening, Dutch Lipid Clinic Network (DLCN), Simon Broome criteria, no active screening). Clinical effectiveness was measured as the number of monogenic FH cases identified. Healthcare costs for each algorithm were evaluated from an NHS England perspective over a 12 week time horizon. The primary outcome was the incremental cost per additional monogenic FH case identified (ICER). FAMCAT2 was found to dominate (cheaper and more effective) cholesterol and FAMCAT1 algorithms, and extendedly dominate DLCN. The ICER for FAMCAT2 vs. no active screening was 8111 GBP (95% CI: 4088 to 14,865), and for Simon Broome vs. FAMCAT2 was 74,059 GBP (95% CI: -1,113,172 to 1,697,142). Simon Broome found the largest number of FH cases yet required 102 genetic tests to identify one FH patient. FAMCAT2 identified fewer, but only required 23 genetic tests.
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Identifiers
What OpenQuestion holds
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.