Determinants of pathological complete response and tumor regression in high-risk breast cancer treated with neoadjuvant radiotherapy and chemotherapy.

医学 放射治疗 乳腺癌 单变量分析 肿瘤科 分级(工程) 化疗 内科学 新辅助治疗 阶段(地层学) 比例危险模型 原发性肿瘤 癌症 多元分析 转移 古生物学 土木工程 工程类 生物
作者
Jan Haussmann,Wilfried Budach,Carolin Nestle Kraemling,Sylvia Wollandt,Danny Jazmati,Bálint Tamaskovics,Stefanie Corradini,Edwin Boelke,Alexander Haussmann,Werner Audretsch,Christiane Matuschek
出处
期刊:Journal of Clinical Oncology [Lippincott Williams & Wilkins]
卷期号:42 (16_suppl): e12652-e12652
标识
DOI:10.1200/jco.2024.42.16_suppl.e12652
摘要

e12652 Background: Pathological complete response (pCR) is a recognized prognostic indicator in breast cancer patients undergoing neoadjuvant systemic therapy (naST). Known determinants of pCR include intrinsic subtype, proliferation index, grading, clinical tumor and nodal stage, as well as the type of systemic therapy. Incorporating neoadjuvant radiotherapy (naRT) may enhance response rates, disease-free survival, toxicity profiles, and cosmetic outcomes compared to adjuvant radiotherapy. However, the factors influencing pCR and primary tumor regression with the addition of neoadjuvant radiotherapy to chemotherapy are not well-documented. Methods: A retrospective analysis was conducted on 341 patients (cT1-cT4/cN0-N+) who received naRT and neoadjuvant chemotherapy between 1990 and 2003. Treatment included naRT to the breast and, in most cases, to the supra-/infraclavicular lymph nodes, complemented by an electron or brachytherapy boost. NaST was administered either sequentially or concurrently with RT, utilizing various regimens. Univariate and multivariate regression analyses were employed to evaluate the impact of different subgroups and treatment modalities on pCR (ypT0/Tis and ypN0) and complete primary tumor response (ypT0/Tis). Receiver operating characteristic (ROC) analysis assessed the interval between radiotherapy (RT) and surgical resection (Rx), as well as the radiotherapy dose. Results: Out of 341 analyzed patients, 31.1% achieved pCR. Multivariate analysis revealed that pCR rates were affected by the planned type of resection, breast cancer subtype, primary tumor stage, and the interval between radiation and surgery. The biologically effective dose to the tumor did not significantly impact pCR. Univariate analysis identified age, resection type, breast cancer subtype, clinical tumor stage, and grading as significant factors for primary tumor regression. In the multivariate analysis, resection type, subtype, and clinical tumor stage remained significant. Radiation dose to the tumor and the interval from radiation to surgery were not significant for pCR. However, a longer interval from radiotherapy to resection significantly predicted pCR when treatment factors were included in the model. Conclusions: The factors associated with pCR following combined neoadjuvant chemotherapy and radiotherapy are akin to those identified with neoadjuvant chemotherapy alone. A prolonged interval to surgery may be linked to higher pCR rates. Escalating the dose beyond 60 Gy did not lead to increased response rates.

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