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Cornel MC, van der Meij KRM, van El CG, Rigter T, Henneman L. Genetic Screening-Emerging Issues. Genes (Basel) 2024; 15:581. [PMID: 38790210 PMCID: PMC11121342 DOI: 10.3390/genes15050581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/25/2024] [Accepted: 04/30/2024] [Indexed: 05/26/2024] Open
Abstract
In many countries, some form of genetic screening is offered to all or part of the population, either in the form of well-organized screening programs or in a less formalized way. Screening can be offered at different phases of life, such as preconception, prenatal, neonatal and later in life. Screening should only be offered if the advantages outweigh the disadvantages. Technical innovations in testing and treatment are driving changes in the field of prenatal and neonatal screening, where many jurisdictions have organized population-based screening programs. As a result, a greater number and wider range of conditions are being added to the programs, which can benefit couples' reproductive autonomy (preconception and prenatal screening) and improve early diagnosis to prevent irreversible health damage in children (neonatal screening) and in adults (cancer and cascade screening). While many developments in screening are technology-driven, citizens may also express a demand for innovation in screening, as was the case with non-invasive prenatal testing. Relatively new emerging issues for genetic screening, especially if testing is performed using DNA sequencing, relate to organization, data storage and interpretation, benefit-harm ratio and distributive justice, information provision and follow-up, all connected to acceptability in current healthcare systems.
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Affiliation(s)
- Martina C. Cornel
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Karuna R. M. van der Meij
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Carla G. van El
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Tessel Rigter
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
| | - Lidewij Henneman
- Section Community Genetics, Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1007 MB Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1100 DD Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Research Institute, 1100 DD Amsterdam, The Netherlands
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Mohammadnia N, Akyea RK, Qureshi N, Bax WA, Cornel JH. Electronic health record-based facilitation of familial hypercholesterolaemia detection sensitivity of different algorithms in genetically confirmed patients. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2022; 3:578-586. [PMID: 36710904 PMCID: PMC9779787 DOI: 10.1093/ehjdh/ztac059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 08/08/2022] [Indexed: 11/05/2022]
Abstract
Aims Familial hypercholesterolaemia (FH) is a disorder of LDL cholesterol clearance, resulting in increased risk of cardiovascular disease. Recently, we developed a Dutch Lipid Clinic Network (DLCN) criteria-based algorithm to facilitate FH detection in electronic health records (EHRs). In this study, we investigated the sensitivity of this and other algorithms in a genetically confirmed FH population. Methods and results All patients with a healthcare insurance-related coded diagnosis of 'primary dyslipidaemia' between 2018 and 2020 were assessed for genetically confirmed FH. Data were extracted at the time of genetic confirmation of FH (T1) and during the first visit in 2018-2020 (T2). We assessed the sensitivity of algorithms on T1 and T2 for DLCN ≥ 6 and compared with other algorithms [familial hypercholesterolaemia case ascertainment tool (FAMCAT), Make Early Diagnoses to Prevent Early Death (MEDPED), and Simon Broome (SB)] using EHR-coded data and using all available data (i.e. including non-coded free text). 208 patients with genetically confirmed FH were included. The sensitivity (95% CI) on T1 and T2 with EHR-coded data for DLCN ≥ 6 was 19% (14-25%) and 22% (17-28%), respectively. When using all available data, the sensitivity for DLCN ≥ 6 was 26% (20-32%) on T1 and 28% (22-34%) on T2. For FAMCAT, the sensitivity with EHR-coded data on T1 was 74% (67-79%) and 32% (26-39%) on T2, whilst sensitivity with all available data was 81% on T1 (75-86%) and 45% (39-52%) on T2. For Make Early Diagnoses to Prevent Early Death MEDPED and SB, using all available data, the sensitivity on T1 was 31% (25-37%) and 17% (13-23%), respectively. Conclusions The FAMCAT algorithm had significantly better sensitivity than DLCN, MEDPED, and SB. FAMCAT has the best potential for FH case-finding using EHRs.
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Affiliation(s)
- Niekbachsh Mohammadnia
- Department of Internal Medicine, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
- Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
- Department of Cardiology, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Ralph K Akyea
- Primary Care Stratified Medicine (PRISM) Research Group, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Applied Health Research Building, University Park, Nottingham NG7 2RD, UK
| | - Nadeem Qureshi
- Primary Care Stratified Medicine (PRISM) Research Group, Centre for Academic Primary Care, School of Medicine, University of Nottingham, Applied Health Research Building, University Park, Nottingham NG7 2RD, UK
| | - Willem A Bax
- Department of Internal Medicine, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
| | - Jan H Cornel
- Department of Cardiology, Northwest Clinics, Wilhelminalaan 12, 1815 JD, Alkmaar, The Netherlands
- Department of Cardiology, Radboudumc, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
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Begic E, Djozic A, Karavelic E, Zatric N, Sinancevic A, Dzubur A, Durak-Nalbantic A, Begic A, Begic N, Sahbaz A, Hasanagic E, Gogic E, Naser N, Zukic F, Medjedovic E, Iglica A, Halilcevic M, Begic Z. Familial hypercholesterolemia within cardiology practice – single-center experience during 2-year period. Res Cardiovasc Med 2022. [DOI: 10.4103/rcm.rcm_19_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Qureshi N, Akyea RK, Dutton B, Leonardi-Bee J, Humphries SE, Weng S, Kai J. Comparing the performance of the novel FAMCAT algorithms and established case-finding criteria for familial hypercholesterolaemia in primary care. Open Heart 2021; 8:openhrt-2021-001752. [PMID: 34635577 PMCID: PMC8506870 DOI: 10.1136/openhrt-2021-001752] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/07/2021] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVE Familial hypercholesterolaemia (FH) is a common inherited disorder causing premature coronary heart disease (CHD) and death. We have developed the novel Familial Hypercholesterolaemia Case Ascertainment Tool (FAMCAT 1) case-finding algorithm for application in primary care, to improve detection of FH. The performance of this algorithm was further improved by including personal history of premature CHD (FAMCAT 2 algorithm). This study has evaluated their performance, at 95% specificity, to detect genetically confirmed FH in the general population. We also compared these algorithms to established clinical case-finding criteria. METHODS Prospective validation study, in 14 general practices, recruiting participants from the general adult population with cholesterol documented. For 260 participants with available health records, we determined possible FH cases based on FAMCAT thresholds, Dutch Lipid Clinic Network (DLCN) score, Simon-Broome criteria and recommended cholesterol thresholds (total cholesterol >9.0 mmol/L if ≥30 years or >7.5 mmol/L if <30 years), using clinical data from electronic and manual extraction of patient records and family history questionnaires. The reference standard was genetic testing. We examined detection rate (DR), sensitivity and specificity for each case-finding criteria. RESULTS At 95% specificity, FAMCAT 1 had a DR of 27.8% (95% CI 12.5% to 50.9%) with sensitivity of 31.2% (95% CI 11.0% to 58.7%); while FAMCAT 2 had a DR of 45.8% (95% CI 27.9% to 64.9%) with sensitivity of 68.8% (95% CI 41.3% to 89.0%). DLCN score ≥6 points yielded a DR of 35.3% (95% CI 17.3% to 58.7%) and sensitivity of 37.5% (95% CI 15.2% to 64.6%). Using recommended cholesterol thresholds resulted in DR of 28.0% (95% CI 14.3% to 47.6%) with sensitivity of 43.8% (95% CI 19.8% to 70.1%). Simon-Broome criteria had lower DR 11.3% (95% CI 6.0% to 20.0%) and specificity 70.9% (95% CI 64.8% to 76.5%) but higher sensitivity of 56.3% (95% CI 29.9% to 80.2%). CONCLUSIONS In primary care, in patients with cholesterol documented, FAMCAT 2 performs better than other case-finding criteria for detecting genetically confirmed FH, with no prior clinical review required for case finding. TRIAL REGISTRATION NUMBER NCT03934320.
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Affiliation(s)
- Nadeem Qureshi
- Primary Care Stratified Medicine (PRISM) Research Group, School of Medicine, University of Nottingham, Nottingham, UK
| | - Ralph K Akyea
- Primary Care Stratified Medicine (PRISM) Research Group, School of Medicine, University of Nottingham, Nottingham, UK
| | - Brittany Dutton
- Primary Care Stratified Medicine (PRISM) Research Group, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jo Leonardi-Bee
- Primary Care Stratified Medicine (PRISM) Research Group, School of Medicine, University of Nottingham, Nottingham, UK,Centre for Evidence Based Healthcare, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK
| | - Steve E Humphries
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Stephen Weng
- Cardiovascular and Metabolism, Janssen Research & Development, High Wycombe, UK
| | - Joe Kai
- Primary Care Stratified Medicine (PRISM) Research Group, School of Medicine, University of Nottingham, Nottingham, UK
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