Publications by authors named "S Z Maron"
Background: F-FDG PET-CT-based host metabolic (PETMet) profiling of non-tumor tissue is a novel approach to incorporate the patient-specific response to cancer into clinical algorithms.
Materials And Methods: A prospectively maintained institutional database of gastroesophageal cancer patients was queried for pretreatment PET-CTs, demographics, and clinicopathologic variables. F-FDG PET avidity was measured in 9 non-tumor tissue types (liver, spleen, 4 muscles, 3 fat locations).
Background: 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 PDFEsophagectomy may have a role in stage IV esophageal adenocarcinoma.
J Thorac Cardiovasc Surg
November 2024
Objective: We sought to determine whether aggressive local treatment provides a benefit in patients with stage IV esophageal adenocarcinoma and to determine factors associated with survival.
Methods: Patients with clinical stage IV esophageal adenocarcinoma at diagnosis who underwent esophagectomy from 2010 to 2023 were identified from our prospectively maintained database. Clinicopathologic and demographic characteristics were compared among patients by stage.
Article Synopsis
- Researchers are merging unstructured patient data with structured health records to create the MSK-CHORD dataset, consisting of varied cancer types from nearly 25,000 patients at Memorial Sloan Kettering Cancer Center.
- This dataset allows for in-depth analysis of cancer outcomes using advanced techniques like natural language processing, revealing new relationships that smaller datasets may not show.
- Using MSK-CHORD for machine learning models, findings suggest that incorporating features from these unstructured texts can better predict patient survival than relying solely on genomic data or cancer staging.
Article Synopsis
- The study examined the effects of the Comprehensive Care for Joint Replacement (CJR) program on patient demographics and outcomes for total hip and knee replacements in New York State.
- Researchers analyzed data before and after CJR implementation, focusing on changes in patient age and health conditions, as well as hospitalization costs and discharge outcomes.
- Results showed that hospitals did not select healthier patients post-CJR; instead, they treated slightly older and more comorbid patients while also observing reduced hospitalization costs and fewer patients being discharged to institutional care.