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Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?

PURPOSE: Results from active surveillance trials for ductal carcinoma in situ (DCIS) will not be available for > 10 years. A model based on real-world data (RWD) can demonstrate the comparative impact of non-intervention for women with low-risk features. METHODS: Multi-state models were developed...

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Autores principales: Byng, Danalyn, Retèl, Valesca P., Schaapveld, Michael, Wesseling, Jelle, van Harten, Wim H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062323/
https://www.ncbi.nlm.nih.gov/pubmed/33389397
http://dx.doi.org/10.1007/s10549-020-06042-1
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author Byng, Danalyn
Retèl, Valesca P.
Schaapveld, Michael
Wesseling, Jelle
van Harten, Wim H.
author_facet Byng, Danalyn
Retèl, Valesca P.
Schaapveld, Michael
Wesseling, Jelle
van Harten, Wim H.
author_sort Byng, Danalyn
collection PubMed
description PURPOSE: Results from active surveillance trials for ductal carcinoma in situ (DCIS) will not be available for > 10 years. A model based on real-world data (RWD) can demonstrate the comparative impact of non-intervention for women with low-risk features. METHODS: Multi-state models were developed using Surveillance, Epidemiology, and End Results Program (SEER) data for three treatment strategies (no local treatment, breast conserving surgery [BCS], BCS + radiotherapy [RT]), and for women with DCIS low-risk features. Eligible cases included women aged ≥ 40 years, diagnosed with primary DCIS between 1992 and 2016. Five mutually exclusive health states were modelled: DCIS, ipsilateral invasive breast cancer (iIBC) ≤ 5 years and > 5 years post-DCIS diagnosis, contralateral IBC, death preceded by and death not preceded by IBC. Propensity score-weighted Cox models assessed effects of treatment, age, diagnosis year, grade, ER status, and race. RESULTS: Data on n = 85,982 women were used. Increased risk of iIBC ≤ 5 years post-DCIS was demonstrated for ages 40–49 (Hazard ratio (HR) 1.86, 95% Confidence Interval (CI) 1.34–2.57 compared to age 50–69), grade 3 lesions (HR 1.42, 95%CI 1.05-1.91) compared to grade 2, lesion size ≥ 2 cm (HR 1.66, 95%CI 1.23–2.25), and Black race (HR 2.52, 95%CI 1.83–3.48 compared to White). According to the multi-state model, propensity score-matched women with low-risk features who had not died or experienced any subsequent breast event by 10 years, had a predicted probability of iIBC as first event of 3.02% for no local treatment, 1.66% for BCS, and 0.42% for BCS+RT. CONCLUSION: RWD from the SEER registry showed that women with primary DCIS and low-risk features demonstrate minimal differences by treatment strategy in experiencing subsequent breast events. There may be opportunity to de-escalate treatment for certain women with low-risk features: Hispanic and non-Hispanic white women aged 50–69 at diagnosis, with ER+, grade 1 + 2, < 2 cm DCIS lesions. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s10549-020-06042-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-80623232021-05-05 Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence? Byng, Danalyn Retèl, Valesca P. Schaapveld, Michael Wesseling, Jelle van Harten, Wim H. Breast Cancer Res Treat Epidemiology PURPOSE: Results from active surveillance trials for ductal carcinoma in situ (DCIS) will not be available for > 10 years. A model based on real-world data (RWD) can demonstrate the comparative impact of non-intervention for women with low-risk features. METHODS: Multi-state models were developed using Surveillance, Epidemiology, and End Results Program (SEER) data for three treatment strategies (no local treatment, breast conserving surgery [BCS], BCS + radiotherapy [RT]), and for women with DCIS low-risk features. Eligible cases included women aged ≥ 40 years, diagnosed with primary DCIS between 1992 and 2016. Five mutually exclusive health states were modelled: DCIS, ipsilateral invasive breast cancer (iIBC) ≤ 5 years and > 5 years post-DCIS diagnosis, contralateral IBC, death preceded by and death not preceded by IBC. Propensity score-weighted Cox models assessed effects of treatment, age, diagnosis year, grade, ER status, and race. RESULTS: Data on n = 85,982 women were used. Increased risk of iIBC ≤ 5 years post-DCIS was demonstrated for ages 40–49 (Hazard ratio (HR) 1.86, 95% Confidence Interval (CI) 1.34–2.57 compared to age 50–69), grade 3 lesions (HR 1.42, 95%CI 1.05-1.91) compared to grade 2, lesion size ≥ 2 cm (HR 1.66, 95%CI 1.23–2.25), and Black race (HR 2.52, 95%CI 1.83–3.48 compared to White). According to the multi-state model, propensity score-matched women with low-risk features who had not died or experienced any subsequent breast event by 10 years, had a predicted probability of iIBC as first event of 3.02% for no local treatment, 1.66% for BCS, and 0.42% for BCS+RT. CONCLUSION: RWD from the SEER registry showed that women with primary DCIS and low-risk features demonstrate minimal differences by treatment strategy in experiencing subsequent breast events. There may be opportunity to de-escalate treatment for certain women with low-risk features: Hispanic and non-Hispanic white women aged 50–69 at diagnosis, with ER+, grade 1 + 2, < 2 cm DCIS lesions. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s10549-020-06042-1) contains supplementary material, which is available to authorized users. Springer US 2021-01-03 2021 /pmc/articles/PMC8062323/ /pubmed/33389397 http://dx.doi.org/10.1007/s10549-020-06042-1 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
Byng, Danalyn
Retèl, Valesca P.
Schaapveld, Michael
Wesseling, Jelle
van Harten, Wim H.
Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?
title Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?
title_full Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?
title_fullStr Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?
title_full_unstemmed Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?
title_short Treating (low-risk) DCIS patients: What can we learn from real-world cancer registry evidence?
title_sort treating (low-risk) dcis patients: what can we learn from real-world cancer registry evidence?
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062323/
https://www.ncbi.nlm.nih.gov/pubmed/33389397
http://dx.doi.org/10.1007/s10549-020-06042-1
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