Publications by authors named "D Coit"
Introduction: Clinicopathologic data-based sentinel lymph node (SLN) prediction models are used to select patients with melanoma for sentinel lymph node biopsy (SLNB). However, the temporal performance of these models is unknown. Therefore, we investigated whether the performance and clinical utility of the Melanoma Institute of Australia, Memorial Sloan Kettering Cancer Center, and Friedman et al.
View Article and Find Full Text PDFBackground: There has been a paradoxical rise in young-onset gastric cancer (YOGC), defined as gastric cancer (GC) diagnosed before age 50. Precursor lesions may contribute to pathogenesis, though their role in progression to different histologic subtypes is unclear. The impact of self-reported race is also poorly characterized and may be unreliable as a proxy for genetic differences.
View Article and Find Full Text PDFArticle Synopsis
- The study aims to analyze the relationship between the Siewert classification of gastroesophageal junction adenocarcinomas and their genomic profiles to better inform staging and treatment decisions.
- The research included 350 patients and found that Siewert type I and II tumors displayed similar genomic features to lower esophageal tumors, while Siewert type III tumors had distinct characteristics more aligned with gastric cancers.
- The findings suggest that molecular classification may be more beneficial than traditional anatomical classification for guiding treatment and improving prognosis in these cancer cases.
Patients undergoing extensive lymph node dissection and radiation are at high risk for not only lymphedema but also painful contracture. In a standard lymphadenectomy, immediate lymphatic reconstruction using a lymphovenous bypass is effective in reconstructing the lymphatic defect. However, a more aggressive nodal clearance leaves the patient with a large cavity and skeletonized neurovascular structures, often resulting in severe contracture, pain, cosmetic deformity, and venous stricture.
View Article and Find Full Text PDFBackground: PET-CT-based patient metabolic profiling is a novel concept to incorporate patient-specific metabolism into gastric cancer care.
Methods: Staging PET-CTs, demographics, and clinicopathologic variables of gastric cancer patients were obtained from a prospectively maintained institutional database. PET-CT avidity was measured in tumor, liver, spleen, four paired muscles, and two paired fat areas in each patient.