A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population
Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Stud...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/15/22/5380 |
| _version_ | 1797459880928346112 |
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| author | Cynthia Mbuya-Bienge Nora Pashayan Cornelia D. Kazemali Julie Lapointe Jacques Simard Hermann Nabi |
| author_facet | Cynthia Mbuya-Bienge Nora Pashayan Cornelia D. Kazemali Julie Lapointe Jacques Simard Hermann Nabi |
| author_sort | Cynthia Mbuya-Bienge |
| collection | DOAJ |
| description | Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices. |
| first_indexed | 2024-03-09T16:57:15Z |
| format | Article |
| id | doaj.art-ffe281d5f48b40118ae7ae55f880f9fb |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-09T16:57:15Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-ffe281d5f48b40118ae7ae55f880f9fb2023-11-24T14:34:10ZengMDPI AGCancers2072-66942023-11-011522538010.3390/cancers15225380A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General PopulationCynthia Mbuya-Bienge0Nora Pashayan1Cornelia D. Kazemali2Julie Lapointe3Jacques Simard4Hermann Nabi5Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, CanadaDepartment of Applied Health Research, University College London, London WC1E 6BT, UKDepartment of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, CanadaOncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, CanadaEndocrinology and Nephology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1V 4G2, CanadaDepartment of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, CanadaSingle nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.https://www.mdpi.com/2072-6694/15/22/5380breast cancerpolygenic risk score (PRS)risk prediction toolsnon-genetic risk factorssystematic review |
| spellingShingle | Cynthia Mbuya-Bienge Nora Pashayan Cornelia D. Kazemali Julie Lapointe Jacques Simard Hermann Nabi A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population Cancers breast cancer polygenic risk score (PRS) risk prediction tools non-genetic risk factors systematic review |
| title | A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population |
| title_full | A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population |
| title_fullStr | A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population |
| title_full_unstemmed | A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population |
| title_short | A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population |
| title_sort | systematic review and critical assessment of breast cancer risk prediction tools incorporating a polygenic risk score for the general population |
| topic | breast cancer polygenic risk score (PRS) risk prediction tools non-genetic risk factors systematic review |
| url | https://www.mdpi.com/2072-6694/15/22/5380 |
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