Comparative analysis of bone and soft tissue vs. visceral synovial sarcoma: Demographic, clinical, and survival outcomes; a retrospective population-based study.

Background: Synovial sarcoma (SS) is typically diagnoses in young adults and usually appears in the extremities and soft tissues. However, it can sometimes arise in visceral organs. This study examines the differences in patient demographics, clinical features, and survival rates between soft tissue and visceral synovial sarcoma.

Acinic Cell Carcinoma in the 21st Century: A Population-Based Study from the SEER Database and Review of Recent Molecular Genetic Advances.

Background: Acinic cell carcinoma (AciCC) comprises 6-7% of all salivary gland neoplasms and is the second most common salivary gland malignancy in children. Like many salivary gland carcinomas, it is considered low grade but occasionally it behaves aggressively. Understanding the risk factors associated with recurrence, metastasis, and death is important to determine the counseling and management of individual patients.

Clinicopathological and Treatment Patterns of Combined Small-Cell Lung Carcinoma with Future Insight to Treatment: A Population-Based Study.

Background: Primary lung cancer is the most common cause of cancer-related mortality in the United States (US). Approximately 90% of lung cancers are associated with smoking and the use of other tobacco products. Based on histology, lung cancers are divided into small-cell lung carcinomas (SCLCs) and non-small-cell lung carcinomas (NSCLCs).

Mucoepidermoid Carcinoma of the Salivary Gland: Demographics and Comparative Analysis in U.S. Children and Adults with Future Perspective of Management.

Background: Salivary gland neoplasms are uncommon in both pediatric and adult populations. Mucoepidermoid carcinoma (MEC) is one of the most common salivary gland tumors and usually presents with atypical clinical features. This study sought to evaluate the demographic and clinical factors affecting outcomes in adults and pediatric populations with MEC that could be used to risk stratification for treatment selection and clinical trial enrollment.