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1.
Turk J Surg ; 38(4): 409-412, 2022 Dec.
Article in English | MEDLINE | ID: mdl-36875268

ABSTRACT

Extraosseous sarcoma of the breast is an infrequent entity and a harbinger of poor prognosis. Histogenesis of this tumor is uncertain, and it can arise both in denovo and metastatic settings. Morphologically, it is indistinguishable from its skeletal counterpart and clinically, it presents like any other subtype of breast cancer. Tumor recurrence with a propensity for hematogenous rather than lymphatic spread plagues with this malicious disease. Treatment guidelines are mainly extrapolations from those of treatment of other extra-skeletal sarcomas as literature is limited in this context. In this study, it was aimed to present two clinical cases with similar clinical profiles and different treatment outcomes. The intent of this case report is to contribute to the limited database available for management of this rare disease.

2.
Breast ; 59: 1-7, 2021 Oct.
Article in English | MEDLINE | ID: mdl-34098459

ABSTRACT

Accurate recurrence risk assessment in hormone receptor positive, HER2/neu negative breast cancer is critical to plan precise therapy. CanAssist Breast (CAB) assesses recurrence risk based on tumor biology using artificial intelligence-based approach. We report CAB risk assessment correlating with disease outcomes in multiple clinically high- and low-risk subgroups. In this retrospective cohort of 925 patients [median age-54 (22-86)] CAB had hazard ratio (HR) of 3 (1.83-5.21) and 2.5 (1.45-4.29), P = 0.0009) in univariate and multivariate analysis. CAB's HR in sub-groups with the other determinants of outcome, T2 (HR: 2.79 (1.49-5.25), P = 0.0001); age [< 50 (HR: 3.14 (1.39-7), P = 0.0008)]. Besides application in node-negative patients, CAB's HR was 2.45 (1.34-4.47), P = 0.0023) in node-positive patients. In clinically low-risk patients (N0 tumors up to 5 cms) (HR: 2.48 (0.79-7.8), P = 0.03) and with luminal-A characteristics (HR: 4.54 (1-19.75), P = 0.004), CAB identified >16% as high-risk with recurrence rates of up to 12%. In clinically high-risk patients (T2N1 tumors (HR: 2.65 (1.31-5.36), P = 0.003; low-risk DMFS: 92.66 ± 1.88) and in women with luminal-B characteristics (HR: 3.24; (1.69-6.22), P < 0.0001; low-risk DMFS: 93.34 ± 1.34)), CAB identified >64% as low-risk. Thus, CAB prognostication was significant in women with clinically low- and high-risk disease. The data imply the use of CAB for providing helpful information to stratify tumors based on biology incorporated with clinical features for Indian patients, which can be extrapolated to regions with similarly characterized patients, South-East Asia.


Subject(s)
Artificial Intelligence , Breast Neoplasms , Biomarkers, Tumor , Female , Humans , Middle Aged , Neoplasm Recurrence, Local , Prognosis , Receptor, ErbB-2 , Receptors, Progesterone , Retrospective Studies
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