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Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study

INTRODUCTION: The response to neoadjuvant chemotherapy (NAC) in breast cancer has important prognostic implications. Dynamic prediction of tumour regression by NAC may allow for adaption of the treatment plan before completion, or even before the start of treatment. Such predictions may help prevent...

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Autores principales: Janssen, Liselore M, Suelmann, Britt B M, Elias, Sjoerd G, Janse, Markus H A, van Diest, Paul J, van der Wall, Elsken, Gilhuijs, Kenneth G A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490628/
https://www.ncbi.nlm.nih.gov/pubmed/36127090
http://dx.doi.org/10.1136/bmjopen-2022-061334
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author Janssen, Liselore M
Suelmann, Britt B M
Elias, Sjoerd G
Janse, Markus H A
van Diest, Paul J
van der Wall, Elsken
Gilhuijs, Kenneth G A
author_facet Janssen, Liselore M
Suelmann, Britt B M
Elias, Sjoerd G
Janse, Markus H A
van Diest, Paul J
van der Wall, Elsken
Gilhuijs, Kenneth G A
author_sort Janssen, Liselore M
collection PubMed
description INTRODUCTION: The response to neoadjuvant chemotherapy (NAC) in breast cancer has important prognostic implications. Dynamic prediction of tumour regression by NAC may allow for adaption of the treatment plan before completion, or even before the start of treatment. Such predictions may help prevent overtreatment and related toxicity and correct for undertreatment with ineffective regimens. Current imaging methods are not able to fully predict the efficacy of NAC. To successfully improve response prediction, tumour biology and heterogeneity as well as treatment-induced changes have to be considered. In the LIMA study, multiparametric MRI will be combined with liquid biopsies. In addition to conventional clinical and pathological information, these methods may give complementary information at multiple time points during treatment. AIM: To combine multiparametric MRI and liquid biopsies in patients with breast cancer to predict residual cancer burden (RCB) after NAC, in adjunct to standard clinico-pathological information. Predictions will be made before the start of NAC, approximately halfway during treatment and after completion of NAC. METHODS: In this multicentre prospective observational study we aim to enrol 100 patients. Multiparametric MRI will be performed prior to NAC, approximately halfway and after completion of NAC. Liquid biopsies will be obtained immediately prior to every cycle of chemotherapy and after completion of NAC. The primary endpoint is RCB in the surgical resection specimen following NAC. Collected data will primarily be analysed using multivariable techniques such as penalised regression techniques. ETHICS AND DISSEMINATION: Medical Research Ethics Committee Utrecht has approved this study (NL67308.041.19). Informed consent will be obtained from each participant. All data are anonymised before publication. The findings of this study will be submitted to international peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04223492.
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spelling pubmed-94906282022-09-22 Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study Janssen, Liselore M Suelmann, Britt B M Elias, Sjoerd G Janse, Markus H A van Diest, Paul J van der Wall, Elsken Gilhuijs, Kenneth G A BMJ Open Oncology INTRODUCTION: The response to neoadjuvant chemotherapy (NAC) in breast cancer has important prognostic implications. Dynamic prediction of tumour regression by NAC may allow for adaption of the treatment plan before completion, or even before the start of treatment. Such predictions may help prevent overtreatment and related toxicity and correct for undertreatment with ineffective regimens. Current imaging methods are not able to fully predict the efficacy of NAC. To successfully improve response prediction, tumour biology and heterogeneity as well as treatment-induced changes have to be considered. In the LIMA study, multiparametric MRI will be combined with liquid biopsies. In addition to conventional clinical and pathological information, these methods may give complementary information at multiple time points during treatment. AIM: To combine multiparametric MRI and liquid biopsies in patients with breast cancer to predict residual cancer burden (RCB) after NAC, in adjunct to standard clinico-pathological information. Predictions will be made before the start of NAC, approximately halfway during treatment and after completion of NAC. METHODS: In this multicentre prospective observational study we aim to enrol 100 patients. Multiparametric MRI will be performed prior to NAC, approximately halfway and after completion of NAC. Liquid biopsies will be obtained immediately prior to every cycle of chemotherapy and after completion of NAC. The primary endpoint is RCB in the surgical resection specimen following NAC. Collected data will primarily be analysed using multivariable techniques such as penalised regression techniques. ETHICS AND DISSEMINATION: Medical Research Ethics Committee Utrecht has approved this study (NL67308.041.19). Informed consent will be obtained from each participant. All data are anonymised before publication. The findings of this study will be submitted to international peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04223492. BMJ Publishing Group 2022-09-20 /pmc/articles/PMC9490628/ /pubmed/36127090 http://dx.doi.org/10.1136/bmjopen-2022-061334 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Oncology
Janssen, Liselore M
Suelmann, Britt B M
Elias, Sjoerd G
Janse, Markus H A
van Diest, Paul J
van der Wall, Elsken
Gilhuijs, Kenneth G A
Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study
title Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study
title_full Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study
title_fullStr Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study
title_full_unstemmed Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study
title_short Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study – a multicentre prospective observational cohort study
title_sort improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric mri: protocol of the lima study – a multicentre prospective observational cohort study
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490628/
https://www.ncbi.nlm.nih.gov/pubmed/36127090
http://dx.doi.org/10.1136/bmjopen-2022-061334
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