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Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data
As randomized trials in the USA and Europe have convincingly demonstrated efficacy of lung cancer screening by computed tomography (CT), European countries are discussing the introduction of screening programs. To maintain acceptable cost-benefit and clinical benefit-to-harm ratios, screening should...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Netherlands
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7524688/ https://www.ncbi.nlm.nih.gov/pubmed/32594286 http://dx.doi.org/10.1007/s10654-020-00657-w |
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author | Hüsing, Anika Kaaks, Rudolf |
author_facet | Hüsing, Anika Kaaks, Rudolf |
author_sort | Hüsing, Anika |
collection | PubMed |
description | As randomized trials in the USA and Europe have convincingly demonstrated efficacy of lung cancer screening by computed tomography (CT), European countries are discussing the introduction of screening programs. To maintain acceptable cost-benefit and clinical benefit-to-harm ratios, screening should be offered to individuals at sufficiently elevated risk of having lung cancer. Using federal-wide survey and lung cancer incidence data (2008–2013), we examined the performance of four well-established risk models from the USA (PLCO(M2012), LCRAT, Bach) and the UK (LLP(2008)) in the German population, comparing with standard eligibility criteria based on age limits, minimal pack years of smoking (or combination of total duration with average intensity) and maximum years since smoking cessation. The eligibility criterion recommended by the United States Preventive Services Taskforce (USPSTF) would select about 3.2 million individuals, a group equal in size to the upper fifth of ever smokers age 50–79 at highest risk, and to 11% of all adults aged 50–79. According to PLCO(M2012), the model showing best concordance between numbers of lung cancer cases predicted and reported in registries, persons with 5-year risk ≥ 1.7% included about half of all lung cancer incidence in the full German population. Compared to eligibility criteria (e.g. USPSTF), risk models elected individuals in higher age groups, including ex-smokers with longer average quitting times. Further studies should address how in Germany these shifts may affect expected benefits of CT screening in terms of life-years gained versus the potential harm of age-specific increasing risk of over-diagnosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10654-020-00657-w) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7524688 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-75246882020-10-14 Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data Hüsing, Anika Kaaks, Rudolf Eur J Epidemiol Screening As randomized trials in the USA and Europe have convincingly demonstrated efficacy of lung cancer screening by computed tomography (CT), European countries are discussing the introduction of screening programs. To maintain acceptable cost-benefit and clinical benefit-to-harm ratios, screening should be offered to individuals at sufficiently elevated risk of having lung cancer. Using federal-wide survey and lung cancer incidence data (2008–2013), we examined the performance of four well-established risk models from the USA (PLCO(M2012), LCRAT, Bach) and the UK (LLP(2008)) in the German population, comparing with standard eligibility criteria based on age limits, minimal pack years of smoking (or combination of total duration with average intensity) and maximum years since smoking cessation. The eligibility criterion recommended by the United States Preventive Services Taskforce (USPSTF) would select about 3.2 million individuals, a group equal in size to the upper fifth of ever smokers age 50–79 at highest risk, and to 11% of all adults aged 50–79. According to PLCO(M2012), the model showing best concordance between numbers of lung cancer cases predicted and reported in registries, persons with 5-year risk ≥ 1.7% included about half of all lung cancer incidence in the full German population. Compared to eligibility criteria (e.g. USPSTF), risk models elected individuals in higher age groups, including ex-smokers with longer average quitting times. Further studies should address how in Germany these shifts may affect expected benefits of CT screening in terms of life-years gained versus the potential harm of age-specific increasing risk of over-diagnosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10654-020-00657-w) contains supplementary material, which is available to authorized users. Springer Netherlands 2020-06-27 2020 /pmc/articles/PMC7524688/ /pubmed/32594286 http://dx.doi.org/10.1007/s10654-020-00657-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Screening Hüsing, Anika Kaaks, Rudolf Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data |
title | Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data |
title_full | Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data |
title_fullStr | Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data |
title_full_unstemmed | Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data |
title_short | Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data |
title_sort | risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of german federal-wide survey and incidence data |
topic | Screening |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7524688/ https://www.ncbi.nlm.nih.gov/pubmed/32594286 http://dx.doi.org/10.1007/s10654-020-00657-w |
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