Pr51 Patterns of Failure in Breast Cancer Patients Treated With Mastectomy Without Radiotherapy

Mehmood, Tahir; Ali, Muhammad; Masood, U.; Shah, Mazhar Ali; Hameed, Shahid; Jamshed, Arif

doi:10.1016/s0960-9776(13)70065-1

Cited by 1 publication

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“…Paper [ 24 ] designed a comparative visual analysis system for patient groups, using automatic statistical data algorithms to explore the similarities and differences between different patient groups under a user-driven analysis strategy. In addition, work on [ 10 ] allows physicians to change medical events in a sequence, such as adding, editing, and deleting, to perform hypothesis analysis to support diagnostic risk prediction. Furthermore, work on event sequence query and recommendation provides technical support for further exploration of EHR data.…”

Section: Related Workmentioning

confidence: 99%

“…Among them, the mammography image recognition technology developed based on imaging histology has effectively completed the intelligent diagnosis of a breast cancer diagnosis. It is expected to solve the problem of regional diagnostic level imbalance in the future [ 10 ]. Multigene models constructed based on transcriptomics and clinical information can achieve accurate prediction of recurrence risk in hormone receptor-positive breast cancer patients [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Value Analysis of Neoadjuvant Radiotherapy for Breast Cancer after Modified Radical Mastectomy Based on Data Mining

Liu

Huang

Pan

et al. 2022

Computational Intelligence and Neuroscience

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Over the last two generations, there has been a surge of interest in nonmutilating treatment for women with early breast cancer. Neoadjuvant radiation therapy, which is progressively being provided to breast cancer patients, could be used to decrease tumor burden while also providing an ability to examine treatment response. This paper aims to explore the effects of the initiation time of radiotherapy after modified adjuvant radical mastectomy on the prognosis of breast cancer. The EMR data can be used to mine hidden rules, which are of great significance for treatment and prognosis analysis. In collaboration with breast cancer, the appropriate prediction model and visualization method are selected and a visual analysis system for breast cancer group and treatment plan based on electronic medical record is constructed. Patients with multiple dimensions are reduced and clustered to form patient groups. The differences of characteristics among patient groups are intuitively displayed by using Nightingale diagram, word cloud, and time axis visualization methods. The support vector machine (SVM) model is used to predict the treatment scheme. The radiotherapy time after modified radical surgery in the two groups was within 15 weeks (observation group) and 15 weeks (routine group), respectively. The incidence of complications, local recurrence rate, progression-free survival, and quality of life scores of patients in the routine group and observation group were compared. The total incidence of complications differed significantly between the observation and routine groups. The physical function, material function, psychological function, and social function of the observation group were significantly higher than the routine group P < 0.05 . Radiotherapy within 15 weeks after modified radical mastectomy for breast cancer can not only reduce the local recurrence rate but also prolong the progression-free survival of patients, and the incidence of complications will not increase, which will greatly help improve the quality of life of patients.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%