Background and objectives Sarcomas represent a heterogeneous group of tumors, and there is lack of data describing contemporary changes in patterns of care. We evaluated the epidemiology of sarcomas over 12 recent years Methods The Surveillance, Epidemiology and End Results (SEER) database was queried for sarcoma cases from 2002-2014. Patient, tumor and treatment factors, and trends over time were studied overall and by subtype. Univariable and multivariable logistic regression models and 5-year survival and cause-specific mortality (CSM) were summarized. Results There were 78,527 cases of sarcomas with an overall incidence of 7.1 cases per 100,000 people, increasing from 6.8 in 2002 to 7.7 in 2014. Sarcoma NOS(14.8%) and soft tissue(43.4%) were the most common histology and primary site, respectively. A majority of tumors were high-grade(33.6%) and >5 cm(51.3%). CSM was 28.6% and 5-year survival was 71.4%. Many patients had unknown-grade(42.2%), which associated with 2.6 times increased odds of no surgical intervention. Conclusions This comprehensive national study highlights important trends including increasing incidence, changing histologic types, and underestimation of true incidence. A large proportion of sarcomas are inadequately staged (unknown-grade 42.2%) with lack of appropriate surgical treatment. Our study highlights need for standardization of care for sarcomas.

Approximately 5-10% of breast cancers may be inheritable, up to 90% of which are due to mutations in BRCA1 and BRCA2. A substantial minority are caused by non-BRCA mutations, such as TP53, PTEN, STK11, CHEK2, ATM, BRIP1, and PALB2 mutations. This review highlights translational research advances with regard to the development of probabilistic models for hereditary breast cancer syndromes, the identification of specific genetic mutations responsible for these syndromes, as well as their testing and interpretations.

Predicting recurrence risk and chemotherapy benefit in early-stage breast cancer is challenging. The Oncotype DX gene assay is often used. Using a database of 221 patients a simple 2-rule model was developed and validated on an independent group of 319 patients. The model categorizes patients unlikely to benefit from the test thus achieving significant avoidance of cost. Background Predicting recurrence risk and chemotherapy benefit in early-stage breast cancer can be challenging, and Oncotype DX (ODX) is often used to gain insight. However, it is still unclear whether ODX can benefit in all cases. To clarify ODX’s usefulness we sought to develop a model using readily available pathologic markers to help clinicians make that determination. Patients and Methods Clinical pathologic data from 221 hormone receptor-positive, HER2-negative invasive breast cancer patients was used to create a model. The model was then validated on a second institution’s set of 319 patients. Results The model has 2 simple rules: low grade and positive progesterone receptor tumors (LG+PR) are low risk, and high grade or low estrogen receptor (ER) (ER < 20%) tumors (HG/LER) are high risk. The TAILORx (Trial Assigning Individualized Options for Treatment (Rx)) trial thresholds of Recurrence Score (RS) ≤ 10, when chemotherapy is of little benefit, and RS ≥ 26 when chemotherapy might be beneficial were used to judge model performance. Impressively, the misclassifications of an HG/LER patient who has an RS ≤ 10 were 0% and 2%, and for LG+PR patients who had an RS ≥ 26 were 0% and 2.6%. In the validation set, 28% (66 of 232) of the indeterminate group (neither in the HG/LER nor the LG + PR groups) had an RS ≤ 10 or an RS ≥ 26; this group might clinically benefit from ODX. Conclusion A simple 2-rule model based on readily available pathologic data was developed and validated, which categorized patients into high and low risk for recurrence. Identification of patients who are unlikely to benefit from ODX testing could result in significant cost avoidance.