% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Haussmann:291985,
author = {J. Haussmann and W. Budach and C. Nestle-Krämling and S.
Wollandt and D. Jazmati and B. Tamaskovics and S. Corradini
and E. Bölke and A. Haussmann$^*$ and W. Audretsch and C.
Matuschek},
title = {{F}actors influencing pathological complete response and
tumor regression in neoadjuvant radiotherapy and
chemotherapy for high-risk breast cancer.},
journal = {Radiation oncology},
volume = {19},
number = {1},
issn = {1748-717X},
address = {London},
publisher = {BioMed Central},
reportid = {DKFZ-2024-01568},
pages = {99},
year = {2024},
abstract = {Pathological complete response (pCR) is a well-established
prognostic factor in breast cancer treated with neoadjuvant
systemic therapy (naST). The determining factors of pCR are
known to be intrinsic subtype, proliferation index, grading,
clinical tumor and nodal stage as well as type of systemic
therapy. The addition of neoadjuvant radiotherapy (naRT) to
this paradigm might improve response, freedom from disease,
toxicity and cosmetic outcome compared to adjuvant
radiotherapy. The factors for pCR and primary tumor
regression when neoadjuvant radiation therapy is added to
chemotherapy have not been thoroughly described.We performed
a retrospective analysis of 341 patients (cT1-cT4/cN0-N+)
treated with naRT and naST between 1990 and 2003. Patients
underwent naRT to the breast and mostly to the
supra-/infraclavicular lymph nodes combined with an electron
or brachytherapy boost. NaST was given either sequentially
or simultaneously to naRT using different regimens. We used
the univariate and multivariate regression analysis to
estimate the effect of different subgroups and treatment
modalities on pCR (ypT0/Tis and ypN0) as well as complete
primary tumor response (ypT0/Tis; bpCR) in our cohort.
Receiver operating characteristic (ROC) analysis was
performed to evaluate the interval between radiotherapy (RT)
and resection (Rx) as well as radiotherapy dose.Out of 341
patients, pCR and pbCR were achieved in $31\%$ and $39\%,$
respectively. pCR rate was influenced by resection type,
breast cancer subtype, primary tumor stage and interval from
radiation to surgery in the multivariate analysis.
Univariate analysis of bpCR showed age, resection type,
breast cancer subtype, clinical tumor stage and grading as
significant factors. Resection type, subtype and clinical
tumor stage remained significant in multivariate analysis.
Radiation dose to the tumor and interval from radiation to
surgery were not significant factors for pCR. However, when
treatment factors were added to the model, a longer interval
from radiotherapy to resection was a significant predictor
for pCR.The factors associated with pCR following naST and
naRT are similar to known factors after naST alone. Longer
interval to surgery might to be associated with higher pCR
rates. Dose escalation beyond 60 Gy did not result in higher
response rates.},
keywords = {Humans / Female / Breast Neoplasms: pathology / Breast
Neoplasms: radiotherapy / Breast Neoplasms: therapy /
Neoadjuvant Therapy / Middle Aged / Retrospective Studies /
Adult / Aged / Radiotherapy, Adjuvant / Prognosis /
Antineoplastic Combined Chemotherapy Protocols: therapeutic
use / Treatment Outcome / ROC Curve / Breast cancer (Other)
/ Breast response (Other) / Neoadjuvant chemotherapy (Other)
/ Neoadjuvant radiotherapy (Other) / pCR (Other)},
cin = {C110},
ddc = {610},
cid = {I:(DE-He78)C110-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:39085866},
pmc = {pmc:PMC11293047},
doi = {10.1186/s13014-024-02450-5},
url = {https://inrepo02.dkfz.de/record/291985},
}