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Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data
PURPOSE: To date, ovarian cancer screening in asymptomatic women has not shown a mortality benefit. The aim of this simulation study was to outline the impact of different histological subtypes on a potential stage-shift, achieved by screening. METHODS: Real-world data were derived in the period of...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782802/ https://www.ncbi.nlm.nih.gov/pubmed/34125280 http://dx.doi.org/10.1007/s00404-021-06117-4 |
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author | Steinkasserer, Lena Irmgard, Delmarko Weiss, Tatjana Dirschlmayer, Walter Mossig, Michael Zeimet, Alain G. Marth, Christian |
author_facet | Steinkasserer, Lena Irmgard, Delmarko Weiss, Tatjana Dirschlmayer, Walter Mossig, Michael Zeimet, Alain G. Marth, Christian |
author_sort | Steinkasserer, Lena |
collection | PubMed |
description | PURPOSE: To date, ovarian cancer screening in asymptomatic women has not shown a mortality benefit. The aim of this simulation study was to outline the impact of different histological subtypes on a potential stage-shift, achieved by screening. METHODS: Real-world data were derived in the period of 2000–2017 from the Klinischen Tumorregister Austria. We estimated five-year overall survival (OS) of patients with ovarian cancer regarding different histological subtypes and FIGO stages. A theoretical model was generated predicting the trend of OS mediated by an eventual down-shifting of ovarian cancer from FIGO stage III/IV to FIGO stage I/II by screening, considering the influence of different histological subtypes. RESULTS: 3458 ovarian cancer patients were subdivided according to histological subtypes and FIGO classification. Major difference in distribution of histological types was found between FIGO stage I/II and III/IV. A theoretical down-shift of tumors from high to low FIGO stages based on our registry calculations showed that the five-year OS would increase from 50% to nearly 80% by perfect screening. CONCLUSION: In our simulation study, we showed that down-shifting ovarian cancers by successful screening might increase OS by 30 percentage point. Our results underscore the importance to recognize ovarian cancer as a heterogenous disease with distinct epidemiologic, molecular and clinical features. The individual characteristic of each histotype is of utmost impact on the definition of screening aims and may influence early detection and stage-shift. Efficacy of screening is mainly dependent on detection of high-risk cancer types and not the slow growing low-grade types. |
format | Online Article Text |
id | pubmed-8782802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-87828022022-02-02 Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data Steinkasserer, Lena Irmgard, Delmarko Weiss, Tatjana Dirschlmayer, Walter Mossig, Michael Zeimet, Alain G. Marth, Christian Arch Gynecol Obstet Gynecologic Oncology PURPOSE: To date, ovarian cancer screening in asymptomatic women has not shown a mortality benefit. The aim of this simulation study was to outline the impact of different histological subtypes on a potential stage-shift, achieved by screening. METHODS: Real-world data were derived in the period of 2000–2017 from the Klinischen Tumorregister Austria. We estimated five-year overall survival (OS) of patients with ovarian cancer regarding different histological subtypes and FIGO stages. A theoretical model was generated predicting the trend of OS mediated by an eventual down-shifting of ovarian cancer from FIGO stage III/IV to FIGO stage I/II by screening, considering the influence of different histological subtypes. RESULTS: 3458 ovarian cancer patients were subdivided according to histological subtypes and FIGO classification. Major difference in distribution of histological types was found between FIGO stage I/II and III/IV. A theoretical down-shift of tumors from high to low FIGO stages based on our registry calculations showed that the five-year OS would increase from 50% to nearly 80% by perfect screening. CONCLUSION: In our simulation study, we showed that down-shifting ovarian cancers by successful screening might increase OS by 30 percentage point. Our results underscore the importance to recognize ovarian cancer as a heterogenous disease with distinct epidemiologic, molecular and clinical features. The individual characteristic of each histotype is of utmost impact on the definition of screening aims and may influence early detection and stage-shift. Efficacy of screening is mainly dependent on detection of high-risk cancer types and not the slow growing low-grade types. Springer Berlin Heidelberg 2021-06-14 2022 /pmc/articles/PMC8782802/ /pubmed/34125280 http://dx.doi.org/10.1007/s00404-021-06117-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Gynecologic Oncology Steinkasserer, Lena Irmgard, Delmarko Weiss, Tatjana Dirschlmayer, Walter Mossig, Michael Zeimet, Alain G. Marth, Christian Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
title | Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
title_full | Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
title_fullStr | Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
title_full_unstemmed | Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
title_short | Efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
title_sort | efficacy of an optimal ovarian cancer screening: a best-case scenario study based on real-world data |
topic | Gynecologic Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782802/ https://www.ncbi.nlm.nih.gov/pubmed/34125280 http://dx.doi.org/10.1007/s00404-021-06117-4 |
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