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Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies
PURPOSE: Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological facto...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945747/ https://www.ncbi.nlm.nih.gov/pubmed/29388015 http://dx.doi.org/10.1007/s10549-018-4693-2 |
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author | Rakovitch, E. Gray, R. Baehner, F. L. Sutradhar, R. Crager, M. Gu, S. Nofech-Mozes, S. Badve, S. S. Hanna, W. Hughes, L. L. Wood, W. C. Davidson, N. E. Paszat, L. Shak, S. Sparano, J. A. Solin, L. J. |
author_facet | Rakovitch, E. Gray, R. Baehner, F. L. Sutradhar, R. Crager, M. Gu, S. Nofech-Mozes, S. Badve, S. S. Hanna, W. Hughes, L. L. Wood, W. C. Davidson, N. E. Paszat, L. Shak, S. Sparano, J. A. Solin, L. J. |
author_sort | Rakovitch, E. |
collection | PubMed |
description | PURPOSE: Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological factors to provide refined estimates of the 10-year risk of LR after treatment by BCS alone. METHODS: Data from E5194 and ODC were combined. Patients with positive margins or multifocality were excluded. Identical Cox regression models were fit for each study. Patient-specific meta-analysis was used to calculate precision-weighted estimates of 10-year LR risk by DS, age, tumor size and year of diagnosis. RESULTS: The combined cohort includes 773 patients. The DS and age at diagnosis, tumor size and year of diagnosis provided independent prognostic information on the 10-year LR risk (p ≤ 0.009). Hazard ratios from E5194 and ODC cohorts were similar for the DS (2.48, 1.95 per 50 units), tumor size ≤ 1 versus > 1–2.5 cm (1.45, 1.47), age ≥ 50 versus < 50 year (0.61, 0.84) and year ≥ 2000 (0.67, 0.49). Utilization of DS combined with tumor size and age at diagnosis predicted more women with very low (≤ 8%) or higher (> 15%) 10-year LR risk after BCS alone compared to utilization of DS alone or clinicopathological factors alone. CONCLUSIONS: The combined analysis provides refined estimates of 10-year LR risk after BCS for DCIS. Adding information on tumor size and age at diagnosis to the DS adjusting for year of diagnosis provides improved LR risk estimates to guide treatment decision making. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10549-018-4693-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5945747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-59457472018-05-15 Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies Rakovitch, E. Gray, R. Baehner, F. L. Sutradhar, R. Crager, M. Gu, S. Nofech-Mozes, S. Badve, S. S. Hanna, W. Hughes, L. L. Wood, W. C. Davidson, N. E. Paszat, L. Shak, S. Sparano, J. A. Solin, L. J. Breast Cancer Res Treat Epidemiology PURPOSE: Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological factors to provide refined estimates of the 10-year risk of LR after treatment by BCS alone. METHODS: Data from E5194 and ODC were combined. Patients with positive margins or multifocality were excluded. Identical Cox regression models were fit for each study. Patient-specific meta-analysis was used to calculate precision-weighted estimates of 10-year LR risk by DS, age, tumor size and year of diagnosis. RESULTS: The combined cohort includes 773 patients. The DS and age at diagnosis, tumor size and year of diagnosis provided independent prognostic information on the 10-year LR risk (p ≤ 0.009). Hazard ratios from E5194 and ODC cohorts were similar for the DS (2.48, 1.95 per 50 units), tumor size ≤ 1 versus > 1–2.5 cm (1.45, 1.47), age ≥ 50 versus < 50 year (0.61, 0.84) and year ≥ 2000 (0.67, 0.49). Utilization of DS combined with tumor size and age at diagnosis predicted more women with very low (≤ 8%) or higher (> 15%) 10-year LR risk after BCS alone compared to utilization of DS alone or clinicopathological factors alone. CONCLUSIONS: The combined analysis provides refined estimates of 10-year LR risk after BCS for DCIS. Adding information on tumor size and age at diagnosis to the DS adjusting for year of diagnosis provides improved LR risk estimates to guide treatment decision making. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10549-018-4693-2) contains supplementary material, which is available to authorized users. Springer US 2018-01-31 2018 /pmc/articles/PMC5945747/ /pubmed/29388015 http://dx.doi.org/10.1007/s10549-018-4693-2 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Epidemiology Rakovitch, E. Gray, R. Baehner, F. L. Sutradhar, R. Crager, M. Gu, S. Nofech-Mozes, S. Badve, S. S. Hanna, W. Hughes, L. L. Wood, W. C. Davidson, N. E. Paszat, L. Shak, S. Sparano, J. A. Solin, L. J. Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies |
title | Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies |
title_full | Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies |
title_fullStr | Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies |
title_full_unstemmed | Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies |
title_short | Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies |
title_sort | refined estimates of local recurrence risks by dcis score adjusting for clinicopathological features: a combined analysis of ecog-acrin e5194 and ontario dcis cohort studies |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945747/ https://www.ncbi.nlm.nih.gov/pubmed/29388015 http://dx.doi.org/10.1007/s10549-018-4693-2 |
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