Investigation of risk factors that cause positive surgical margins in patients who have been operated for breast cancer and discussion of the need for RE-operation
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
Aim: Breast cancer is the most common malignancy among women and despite the fact that clinicians' success of the disease management it is still significant cause of morbidity and mortality worldwide. This study aims to define factors that cause positive resection margin status in patients who have undergone breast conserving surgery due to invasive breast cancer /ductal carcinoma in-situ and after dividing into two groups (who have undergone a second surgery or reexsicion to achieve negative resection margin and who have gone to adjuvant therapies without any reoperations or additional resections) to compare in terms of local recurrence, systemic recurrence and overall survival. Materials and Methods: In this study we examined retrospectively 2242 patients pathology reports who have undergone any breast operations at the Ankara University Faculty of Medicine Hospitals between January 2008 and December 2020 due to breast malignancy. We included only positive resection margin group( invasive cancer cells or ductal carcinoma in-situ component closer than 1 mm to the margin ) and excluded to whom had received neoadjuvant therapies, have had found systemic disease evidence at the diagnosis. Positive resection margin group were seperated into two groups; who have undergone a second surgery to achieve negative resection margin and who have gone to adjuvant therapies without any operations; to analyze these two groups we investigated patients' final margin status and after that we compared final margin negative and final margin positive groups in terms of local recurrence, systemic recurrence and overall survival. Results: After comparision between final margin negative and positive groups we found that local recurrance rate, systemic recurrence rate and mortality rate was not statistically significantly different in between two groups ( P=0,080; P=0,101; P=0,146). Between groups survival rates were not statistically significantly different. (P=0,083). In the final margin negative group average survival months were 163 (158-168) and other group who have positive resection margin survival months were 150 (140-160). Conclusions: In the management of breast cancer patients who have undergone breast conserving surgery if the final pathology reports suggest positive resection margin instead of recommending another surgery and reexsicion in selected patients group clinicians may direct the patients to adjuvant therapies since there is no difference between local recurrence, systemic recurrence and mortality rates. Patients must be informed about the process by clinicans and definetly take a role in desicion making since the reoperation process is both mentally challenging and have worse cosmetic outcomes. Key Words: Breast cancer, positive resection margin, local recurrence, invasive ductal carcinom, breast conversing surgery.
Author
Ayşe Sena Çalış
How to Cite
Ayşe Sena Çalış (Medical Specialty Thesis). Investigation of risk factors that cause positive surgical margins in patients who have been operated for breast cancer and discussion of the need for RE-operation, 2023, Ankara University.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Ankara University
- Avrupa konvansiyonel kuvvetler anlaşması ve Türkiye’ye etkileri (1990-2010)(2011)
- The effects of the demographic development between 1935?2007 on land use and land cover change in the Boğali catchment(2010)
- Investigation of Cankiri Gökdere watershed characteristics and some hydrophysical soil properties(2010)
- The principle of equality of belligerents in international humanitarian law(2023)
- Investigation of student views on the application of the flipped classroom method in medical microbiology lesson(2023)
- Evaporation modelling of lake Turkana using artificial neural networks (ANNs) based on climate projections(2023)