Cargando…
Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model
PURPOSE: To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. METHODS: Data on wo...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505302/ https://www.ncbi.nlm.nih.gov/pubmed/34338943 http://dx.doi.org/10.1007/s10549-021-06335-z |
_version_ | 1784581505569259520 |
---|---|
author | Völkel, Vinzenz Hueting, Tom A. Draeger, Teresa van Maaren, Marissa C. de Munck, Linda Strobbe, Luc J. A. Sonke, Gabe S. Schmidt, Marjanka K. van Hezewijk, Marjan Groothuis-Oudshoorn, Catharina G. M. Siesling, Sabine |
author_facet | Völkel, Vinzenz Hueting, Tom A. Draeger, Teresa van Maaren, Marissa C. de Munck, Linda Strobbe, Luc J. A. Sonke, Gabe S. Schmidt, Marjanka K. van Hezewijk, Marjan Groothuis-Oudshoorn, Catharina G. M. Siesling, Sabine |
author_sort | Völkel, Vinzenz |
collection | PubMed |
description | PURPOSE: To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. METHODS: Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples. RESULTS: Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74–0.76) and SP (0.67, 95%CI: 0.65–0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77–0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created. CONCLUSIONS: INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10549-021-06335-z. |
format | Online Article Text |
id | pubmed-8505302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-85053022021-10-19 Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model Völkel, Vinzenz Hueting, Tom A. Draeger, Teresa van Maaren, Marissa C. de Munck, Linda Strobbe, Luc J. A. Sonke, Gabe S. Schmidt, Marjanka K. van Hezewijk, Marjan Groothuis-Oudshoorn, Catharina G. M. Siesling, Sabine Breast Cancer Res Treat Epidemiology PURPOSE: To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. METHODS: Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples. RESULTS: Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74–0.76) and SP (0.67, 95%CI: 0.65–0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77–0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created. CONCLUSIONS: INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10549-021-06335-z. Springer US 2021-08-02 2021 /pmc/articles/PMC8505302/ /pubmed/34338943 http://dx.doi.org/10.1007/s10549-021-06335-z 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 | Epidemiology Völkel, Vinzenz Hueting, Tom A. Draeger, Teresa van Maaren, Marissa C. de Munck, Linda Strobbe, Luc J. A. Sonke, Gabe S. Schmidt, Marjanka K. van Hezewijk, Marjan Groothuis-Oudshoorn, Catharina G. M. Siesling, Sabine Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model |
title | Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model |
title_full | Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model |
title_fullStr | Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model |
title_full_unstemmed | Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model |
title_short | Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model |
title_sort | improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the influence 2.0 model |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505302/ https://www.ncbi.nlm.nih.gov/pubmed/34338943 http://dx.doi.org/10.1007/s10549-021-06335-z |
work_keys_str_mv | AT volkelvinzenz improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT huetingtoma improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT draegerteresa improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT vanmaarenmarissac improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT demuncklinda improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT strobbelucja improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT sonkegabes improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT schmidtmarjankak improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT vanhezewijkmarjan improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT groothuisoudshoorncatharinagm improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model AT sieslingsabine improvedriskestimationoflocoregionalrecurrencesecondarycontralateraltumorsanddistantmetastasesinearlybreastcancertheinfluence20model |