P185 Breast cancer treatment program: intermediate dose autologous transplants and a non-myeloablative reduced intensity allogeneic transplant integrated in the therapy for early breast cancer

The Breast ◽  
2007 ◽  
Vol 16 ◽  
pp. S66
Author(s):  
M. Van Hoef
2020 ◽  
Author(s):  
Qing Yang ◽  
Ting Luo ◽  
Wei Zhang ◽  
Xiaorong Zhong ◽  
Ping He ◽  
...  

Abstract Background: Due to the multidimensional, multilayered, and chronological order of the cancer data in this study, it was challenging for us to extract treatment paths. Therefore, it was necessary to design a new data mining scheme to effectively extract the treatment path of breast cancer. To determine whether the cSPADE algorithm and system clustering proposed in this study can effectively identify the treatment pathways for early breast cancer. Methods: We applied data mining technology to the electronic medical records of 6891 early breast cancer patients to mine treatment pathways. We provided a method of extracting data from EMR and performed three-stage mining: determining the treatment stage through the cSPADE algorithm → system clustering for treatment plan extraction → cSPADE mining sequence pattern for treatment. The Kolmogorov-Smirnov test and correlation analysis were used to cross-validate the sequence rules of early breast cancer treatment pathways.Results: We unearthed 55 sequence rules for early breast cancer treatment, 3 preoperative neoadjuvant chemotherapy regimens, 3 postoperative chemotherapy regimens, and 2 chemotherapy regimens for patients without surgery. Through 5-fold cross-validation, Pearson and Spearman correlation tests were performed. At the significance level of P <0.05, all correlation coefficients of support, confidence and lift were greater than 0.89. Using the Kolmogorov-Smirnov test, we found no significant differences between the sequence distributions.Conclusions: The cSPADE algorithm combined with system clustering can achieve hierarchical and vertical mining of breast cancer treatment models. By uncovering the treatment pathways of early breast cancer patients by this method, the real-world breast cancer treatment behavior model can be evaluated, and it can provide a reference for the redesign and optimization of the treatment pathways.


2006 ◽  
Vol 26 (6) ◽  
pp. 589-598 ◽  
Author(s):  
Edwin G. Wilkins ◽  
Julie C. Lowery ◽  
Laurel A. Copeland ◽  
Sherry L. Goldfarb ◽  
Patricia A. Wren ◽  
...  

Breast Care ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. 103-110 ◽  
Author(s):  
Marija Balic ◽  
Christoph Thomssen ◽  
Rachel Würstlein ◽  
Michael Gnant ◽  
Nadia Harbeck

This year, the St. Gallen Consensus Conference on early breast cancer treatment standards took place for the third time in Vienna, Austria, which is where the next conference will also take place (next date: March 17–20, 2021!). Once again, more than 3,000 participants from over 100 countries came together, and, overall, the 2019 St. Gallen/Vienna conference was a great success. After 3 days of reviews conducted by a global faculty concerning the most important evidence published in the last 2 years, the Consensus votes’ challenge was to define the impact on routine everyday practice. This year, the conference’s main theme was the optimization of early breast cancer therapies by assessment of the magnitude of benefit, aiming at further refinement when compared to de-escalation and escalation, which were mainly the topic of the 2017 conference. Patient empowerment and the importance of shared decision-making were particularly emphasized. The traditional panel votes were moderated by Eric Winer from Harvard, and for the most part, they managed to clarify most of the critical questions. This brief report by Editors of Breast Care summarizes the results of the 2019 international panel votes with respect to locoregional and systemic treatment as a quick news update for our readers, but it expressly does not intend to replace the official St. Gallen Consensus publication that will follow shortly in Annals of Oncology.


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