Major complications after intraoperative radiotherapy with low-energy x-rays in early breast cancer

Berger, Laura; Grimm, Anja; Sütterlin, Marc; Spaich, Saskia; Sperk, Elena; Tuschy, Benjamin; Berlit, Sebastian

doi:10.1007/s00066-023-02128-z

Cited by 5 publications

(3 citation statements)

References 48 publications

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“…The most common treatment-related effects were fibrosis and mild local tissue pain (both occurring in less than 30% of patients). One case of skin infection was observed which is less frequent compared to other IORT studies [ 18 , 19 ]. No grade 3 and above adverse effects such as lymphedema or telangiectasia were seen in any patients according to the LENT-SOMA grading scale for toxicity.…”

Section: Resultsmentioning

confidence: 65%

Application of Intraoperative Radiotherapy in Early‐Stage Breast Cancer Patients in a Clinical Setting

Wang,

Quint,

Kukeev

et al. 2024

International Journal of Breast Cancer

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Background: Intraoperative radiation therapy (IORT) has gained popularity in recent years as an alternative to external beam whole breast radiation therapy (WBRT) for early‐stage breast cancer. Here, we report 43‐month recurrence and survival outcomes in a multiethnic cohort treated with IORT in a clinical context.Method: Two hundred and eleven patients with low‐risk features were treated with IORT for early‐stage breast cancer from 2014 to 2021. Selection criteria were based on Group Europeen de Curietherapie‐European Society for Therapeutic Radiology and Oncology (GEC‐ESTRO) guidelines: preferably unifocal intraductal carcinoma (IDC), aged > 50, tumor size ≤ 2.0 cm, and without lymph node involvement. All patients received 20 Gy of radiation dose during the lumpectomy. Information on patient and tumor characteristics was collected.Results: The mean age of this cohort was 67.5 years; 95.2% of patients are Jewish, and the rest are Bedouins (4.7%). Most tumors were intraductal carcinoma (97.2%) and stage 1 (94.8%). The mean follow‐up time was 43.4 months. Bedouins had larger tumor sizes (mean 1.21 vs. 1.13 cm) and were younger at diagnosis than Jewish patients (mean 65.4 vs. 67.6 years), although the differences are not significant. The overall recurrence rate was 1.4%. One case of local recurrence (0.5%) and two cases of metastasis (0.9%) were observed during the study period. One patient died from metastasis.Conclusion: Our findings suggest that IORT in selected low‐risk patients can achieve an excellent prognosis with low rates of recurrence and metastasis.

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Section: Resultsmentioning

confidence: 65%

Application of Intraoperative Radiotherapy in Early‐Stage Breast Cancer Patients in a Clinical Setting

Wang,

Quint,

Kukeev

et al. 2024

International Journal of Breast Cancer

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“…A limitation of IORT boost compared to other techniques may be the very limited volume of irradiated tissue, making an assessment of the tumor cavity during surgery crucial. Also, the high single dose needs to be carefully prescribed with a certain distance to the skin [ 38 ]. On the other hand, IORT boost with kV X-rays provides immediate irradiation and very good volume definition.…”

Section: Discussionmentioning

confidence: 99%

Acute and Long-Term Toxicity after Planned Intraoperative Boost and Whole Breast Irradiation in High-Risk Patients with Breast Cancer—Results from the Targeted Intraoperative Radiotherapy Boost Quality Registry (TARGIT BQR)

Goerdt,

Schnaubelt,

Kraus-Tiefenbacher

et al. 2024

Cancers

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In the context of breast cancer treatment optimization, this study prospectively examines the feasibility and outcomes of utilizing intraoperative radiotherapy (IORT) as a boost in combination with standard external beam radiotherapy (EBRT) for high-risk patients. Different guidelines recommend such a tumor bed boost in addition to whole breast irradiation with EBRT for patients with risk factors for local breast cancer recurrence. The TARGIT BQR (NCT01440010) is a prospective, multicenter registry study aimed at ensuring the quality of clinical outcomes. It provides, for the first time, data from a large cohort with a detailed assessment of acute and long-term toxicity following an IORT boost using low-energy X-rays. Inclusion criteria encompassed tumors up to 3.5 cm in size and preoperative indications for a boost. The IORT boost, administered immediately after tumor resection, delivered a single dose of 20 Gy. EBRT and systemic therapy adhered to local tumor board recommendations. Follow-up for toxicity assessment (LENT SOMA criteria: fibrosis, teleangiectasia, retraction, pain, breast edema, lymphedema, hyperpigmentation, ulceration) took place before surgery, 6 weeks to 90 days after EBRT, 6 months after IORT, and then annually using standardized case report forms (CRFs). Between 2011 and 2020, 1133 patients from 10 centers were preoperatively enrolled. The planned IORT boost was conducted in 90%, and EBRT in 97% of cases. Median follow-up was 32 months (range 1–120, 20.4% dropped out), with a median age of 61 years (range 30–90). No acute grade 3 or 4 toxicities were observed. Acute side effects included erythema grade 1 or 2 in 4.4%, palpable seroma in 9.1%, punctured seroma in 0.3%, and wound healing disorders in 2.1%. Overall, chronic teleangiectasia of any grade occurred in 16.2%, fibrosis grade ≥ 2 in 14.3%, pain grade ≥ 2 in 3.4%, and hyperpigmentation in 1.1%. In conclusion, a tumor bed boost through IORT using low-energy X-rays is a swift and feasible method that demonstrates low rates in terms of acute or long-term toxicity profiles in combination with whole breast irradiation.

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“…Existing therapeutic strategies for cancer encompasses surgical interventions, radiation, chemotherapy, and immunotherapy. But they frequently present a myriad of complications ( Berger et al, 2023 ). These include infections, pronounced immunosuppression, bleeding, and other severe side effects that jeopardize patient wellbeing ( Timmons and Hewage, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

ACPPfel: Explainable deep ensemble learning for anticancer peptides prediction based on feature optimization

Liu,

Wu,

et al. 2024

Front. Genet.

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Background: Cancer is a significant global health problem that continues to cause a high number of deaths worldwide. Traditional cancer treatments often come with risks that can compromise the functionality of vital organs. As a potential alternative to these conventional therapies, Anticancer peptides (ACPs) have garnered attention for their small size, high specificity, and reduced toxicity, making them as a promising option for cancer treatments.Methods: However, the process of identifying effective ACPs through wet-lab screening experiments is time-consuming and requires a lot of labor. To overcome this challenge, a deep ensemble learning method is constructed to predict anticancer peptides (ACPs) in this study. To evaluate the reliability of the framework, four different datasets are used in this study for training and testing. During the training process of the model, integration of feature selection methods, feature dimensionality reduction measures, and optimization of the deep ensemble model are carried out. Finally, we explored the interpretability of features that affected the final prediction results and built a web server platform to facilitate anticancer peptides prediction, which can be used by all researchers for further studies. This web server can be accessed at http://lmylab.online:5001/.Results: The result of this study achieves an accuracy rate of 98.53% and an AUC (Area under Curve) value of 0.9972 on the ACPfel dataset, it has improvements on other datasets as well.

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Major complications after intraoperative radiotherapy with low-energy x-rays in early breast cancer

Cited by 5 publications

References 48 publications

Application of Intraoperative Radiotherapy in Early‐Stage Breast Cancer Patients in a Clinical Setting

Application of Intraoperative Radiotherapy in Early‐Stage Breast Cancer Patients in a Clinical Setting

Acute and Long-Term Toxicity after Planned Intraoperative Boost and Whole Breast Irradiation in High-Risk Patients with Breast Cancer—Results from the Targeted Intraoperative Radiotherapy Boost Quality Registry (TARGIT BQR)

ACPPfel: Explainable deep ensemble learning for anticancer peptides prediction based on feature optimization

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