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Jermy B, Läll K, Wolford BN, Wang Y, Zguro K, Cheng Y, Kanai M, Kanoni S, Yang Z, Hartonen T, Monti R, Wanner J, Youssef O, Lippert C, van Heel D, Okada Y, McCartney DL, Hayward C, Marioni RE, Furini S, Renieri A, Martin AR, Neale BM, Hveem K, Mägi R, Palotie A, Heyne H, Mars N, Ganna A, Ripatti S. A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk. Nat Commun 2024; 15:5007. [PMID: 38866767 PMCID: PMC11169548 DOI: 10.1038/s41467-024-48938-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 05/17/2024] [Indexed: 06/14/2024] Open
Abstract
Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.
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Affiliation(s)
- Bradley Jermy
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Brooke N Wolford
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristina Zguro
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Zhiyu Yang
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Tuomo Hartonen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Remo Monti
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Julian Wanner
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Omar Youssef
- Helsinki Biobank, Hospital District of Helsinki and Uusimaa (HUS), Helsinki, Finland
- Pathology Department, University of Helsinki, Helsinki, Finland
| | - Christoph Lippert
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
- Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Simone Furini
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | - Alessandra Renieri
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Medical Genetics, University of Siena, Siena, Italy
- Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Henrike Heyne
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
- Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nina Mars
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland.
- Massachusetts General Hospital, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland.
- Massachusetts General Hospital, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Public Health, University of Helsinki, Helsinki, Finland.
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Šavrova A, Jaal J, Nõmm O, Innos K. Factors associated with advanced-stage diagnosis of cervical cancer in Estonia: a population-based study. Public Health 2023; 225:369-375. [PMID: 37989009 DOI: 10.1016/j.puhe.2023.10.025] [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: 07/05/2023] [Revised: 10/07/2023] [Accepted: 10/11/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVES Cervical cancer (CC) remains a crucial public health issue in Estonia, with high incidence and late diagnosis. The aim of this study was to examine time trends of stage-specific CC incidence in Estonia and factors associated with advanced-stage diagnosis of CC. STUDY DESIGN This was a nationwide population-based retrospective study. METHODS Data on CC cases diagnosed in Estonia in 2007-2018 were obtained from the Estonian Cancer Registry, including tumour, nodes, metastases stage at diagnosis. Sociodemographic data were obtained from the Population Registry. To estimate the risk of advanced-stage diagnosis (stages II-IV vs stage I) associated with sociodemographic factors, Poisson regression with robust variance was used to calculate univariate and multivariate prevalence ratios (PR) with 95% confidence intervals (CIs). Time trends of stage-specific CC incidence for 2005-2019 were examined with joinpoint analysis. RESULTS Incidence of stage I CC showed a significant decline of 4.9% per year since 2007, whereas no change was seen for other stages. Of the 2046 women diagnosed in 2007-2018, 1137 (55.6%) were diagnosed at an advanced stage; this proportion increased from 51% in 2007-2009 to 58% in 2015-2018 (P = 0.004). Multivariate regression analysis showed that advanced-stage diagnosis was associated with age (PR 2.16, 95% CI 1.87-2.49 for women aged ≥75 years compared with those aged 30-44 years), educational level (PR 1.32, 95% CI 1.15-1.51 for women with basic/primary education compared to university education) and marital status (PR 1.14, 95% CI 1.01-1.29 for single women compared to married/cohabiting women). No associations were observed by region of residence or nationality. CONCLUSIONS To reduce CC mortality, it is crucial to improve prevention and early diagnosis of CC in Estonia through human papillomavirus vaccination and effective and quality-assured screening particularly targeting high-risk groups as well as encouraging symptom awareness and regular check-ups among older women.
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Affiliation(s)
- A Šavrova
- North Estonia Medical Centre Foundation, Womens Clinic, J. Sütiste tee 19, 13419, Tallinn, Estonia.
| | - J Jaal
- Institute of Clinical Medicine, University of Tartu, L, Puusepa 8, 50406, Tartu, Estonia
| | - O Nõmm
- National Institute for Health Development, Department of Epidemiology and Biostatistics, Hiiu 42, 11619, Tallinn, Estonia
| | - K Innos
- National Institute for Health Development, Department of Epidemiology and Biostatistics, Hiiu 42, 11619, Tallinn, Estonia
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Shahrabi Farahani F, Paapsi K, Innos K. The impact of sociodemographic factors on the utilization of radiation therapy in breast cancer patients in Estonia: a register-based study. Int J Equity Health 2021; 20:152. [PMID: 34193144 PMCID: PMC8247084 DOI: 10.1186/s12939-021-01497-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 06/11/2021] [Indexed: 11/18/2022] Open
Abstract
Background Radiation therapy is an important part of multimodal breast cancer treatment. The aim was to examine the impact of sociodemographic factors on radiation therapy use in breast cancer (BC) patients in Estonia, linking cancer registry data to administrative databases. Methods Estonian Cancer Registry provided data on women diagnosed with BC in Estonia in 2007–2018, including TNM stage at diagnosis. Use of radiation therapy within 12 months of diagnosis was determined from Estonian Health Insurance Funds claims, and sociodemographic characteristics from population registry. Receipt of radiation therapy was evaluated over time and by clinical and sociodemographic factors. Poisson regression with robust variance was used to calculate univariate and multivariate prevalence rate ratios (PRR) with 95 % confidence intervals (CI) for receipt of radiation therapy among stage I–III BC patients age < 70 years who underwent primary surgery. Results Overall, of 8637 women included in the study, 4310 (50 %) received radiation therapy within 12 months of diagnosis. This proportion increased from 39 to 58 % from 2007 to 2009 to 2016–2018 (p < 0.001). Multivariate regression analysis showed that compared to women with stage I BC, those with more advanced stage were less likely to receive radiation therapy. Receipt of radiation therapy increased significantly over time and was nearly 40 % higher in 2016–2018 than in 2007–2009. Use of radiation therapy was significantly lower for women with the lowest level of education compared to those with a university degree (PRR 0.88, 95 % CI 0.80–0.97), and for divorced/widowed women (PRR 0.95, 95 % CI 0.91–0.99) and single women (PRR 0.92, 95 % CI 0.86–0.99), compared to married women. Age at diagnosis, nationality and place of residence were not associated with receipt of radiation therapy. Conclusions The study showed considerable increase in the use of radiation therapy in Estonia over the study period, which is in line with increases in available equipment. The lack of geographic variations suggests equal access to therapy for patients living in remote regions. However, educational level and marital status were significantly associated with receipt of radiation therapy, highlighting the importance of psychosocial support in ensuring equal access to care.
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Affiliation(s)
- Fereshteh Shahrabi Farahani
- School of Information Technologies, Department of Health Technologies, Tallinn University of Technology, Digital Health MSc Programme, Tallinn, Estonia
| | - Keiu Paapsi
- Department of Epidemiology and Biostatistics, National Institute for Health Development, Hiiu 42, 11619, Tallinn, Estonia
| | - Kaire Innos
- Department of Epidemiology and Biostatistics, National Institute for Health Development, Hiiu 42, 11619, Tallinn, Estonia.
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Idavain J, Lang K, Tomasova J, Lang A, Orru H. Cancer Incidence Trends in the Oil Shale Industrial Region in Estonia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E3833. [PMID: 32481656 PMCID: PMC7312168 DOI: 10.3390/ijerph17113833] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/15/2020] [Accepted: 05/23/2020] [Indexed: 02/07/2023]
Abstract
Large oil shale resources are found in Eastern Estonia, where the mineral resource is mined, excavated, and used for electricity generation and shale oil extraction. During industrial activities in the last 100 years, pollutants have been emitted in large amounts, some of which are toxic and carcinogenic. The current study aims to analyse time trends in cancer incidence in the oil shale industry-affected areas and compare them with overall cancer incidence rates and trends in Estonia. We analysed Estonian Cancer Registry data on selected cancer sites that have been previously indicated to have relationships with industrial activities like oil shale extraction. We included lung cancer, kidney cancer, urinary bladder cancer, leukaemia, breast cancer, and non-Hodgkin's lymphoma. A statistically significantly higher lung cancer age-standardized incidence rate (ASIR) was found during the study period (1992-2015) only in males in the oil shale areas as compared to males in Estonia overall: 133.6 and 95.5 per 100,000, respectively. However, there appeared to be a statistically significant (p < 0.05) decrease in the lung cancer ASIR in males in the oil shale areas (overall decrease 28.9%), whereas at the same time, there was a significant increase (p < 0.05) in non-oil shale areas (13.3%) and in Estonia overall (1.5%). Other cancer sites did not show higher ASIRs in the oil shale industrial areas compared to other areas in Estonia. Possible explanations could be improved environmental quality, socio-economic factors, and other morbidities.
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Affiliation(s)
- Jane Idavain
- Institute of Family Medicine and Public Health, Faculty of Medicine, University of Tartu, Ravila 19, 50411 Tartu, Estonia; (K.L.); (H.O.)
- Department of Health Statistics, National Institute for Health Development, Hiiu 42, 11619 Tallinn, Estonia
| | - Katrin Lang
- Institute of Family Medicine and Public Health, Faculty of Medicine, University of Tartu, Ravila 19, 50411 Tartu, Estonia; (K.L.); (H.O.)
| | - Jelena Tomasova
- Estonian Health Board, Paldiski mnt 81, 10617 Tallinn, Estonia;
| | - Aavo Lang
- Institute of Biomedicine and Translational Medicine, Faculty of Medicine, University of Tartu, Ravila 19, 50411 Tartu, Estonia;
| | - Hans Orru
- Institute of Family Medicine and Public Health, Faculty of Medicine, University of Tartu, Ravila 19, 50411 Tartu, Estonia; (K.L.); (H.O.)
- Department of Public Health and Clinical Medicine, Umea University, SE-901 87 Umea, Sweden
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Baburin A, Aareleid T, Rahu M, Reedik L, Innos K. Recent changes in breast cancer incidence and mortality in Estonia: Transition to the west. Acta Oncol 2016; 55:728-33. [PMID: 27222251 DOI: 10.3109/0284186x.2015.1125014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background The aim of this study was to examine breast cancer (BC) incidence and mortality trends in Estonia during recent decades and to compare the pattern of these trends with other selected European countries and regions. We attempt to explain the findings in relation to changes in Estonian society and healthcare system. Methods BC incidence (1985-2012) and mortality (1985-2013) data for Estonia were obtained from the Estonian Cancer Registry and Statistics Estonia. Data for selected European countries were obtained from the EUREG database. Joinpoint regression was used to analyze age-standardized rates in Estonia by age. For international comparison of incidence and mortality rates, we used scatterplot with 95% confidence ellipses and the mortality to incidence ratio. Results The overall BC incidence continues to increase in Estonia, while mortality has been in decline since 2000. Both incidence and mortality trends varied considerably across age groups. Among women aged 60 years and older, BC incidence increased at a rate of nearly 3% per year. Significant decrease in mortality was seen only among women aged 50-59 years. Comparison of scatterplots between countries and regions revealed two clusters in Europe separated along the incidence axis. The correlation between incidence and mortality in Estonia changed its direction in the mid-1990s. Conclusion In recent years, the dynamics of BC burden in Estonia has transitioned towards the high incidence-low mortality type model, which is characteristic to Western, Northern and Southern Europe. Although overall BC incidence is much lower in Estonia than in more affluent European countries, mortality from BC is still relatively high, particularly among elderly women.
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Affiliation(s)
- Aleksei Baburin
- Department of Epidemiology and Biostatistics, National Institute for Health Development, Hiiu 42, Tallinn, 11619, Estonia
| | - Tiiu Aareleid
- Department of Epidemiology and Biostatistics, National Institute for Health Development, Hiiu 42, Tallinn, 11619, Estonia
| | - Mati Rahu
- Department of Epidemiology and Biostatistics, National Institute for Health Development, Hiiu 42, Tallinn, 11619, Estonia
| | - Lauri Reedik
- Department of Public Health, University of Tartu, Tartu, Estonia
| | - Kaire Innos
- Department of Epidemiology and Biostatistics, National Institute for Health Development, Hiiu 42, Tallinn, 11619, Estonia
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