Introduction: Renal cell carcinoma can invade through the renal vein into the inferior vena cava, and can extend intraluminally, with tumor-thrombus formation.
Methods: Retrospective study from January 2003 to August 2016. Surgical outcomes were analyzed. Neves classification was used for patient categorization. Kaplan Meier and Log-Rank test were used for survival analysis.
Results: A total of 134 patients were included, 69 males (51.4%) and 65 females (49%), M:F ratio 1.06:1. Tumor size, bleeding and surgical time were higher in level IV thrombi (mean 16.1cm, 3 064ml and 6.5hrs, respectively), compared to level I (8.5cm, 1033ml and 3.1hrs, respectively). A higher frequency of positive lymph nodes was observed in levels III and IV compared with levels I and II (49% vs. 17.7%, p=0.0001). Distant metastases were observed in 36 pts. (27%). Overall surgical mortality was 4.5%. 5-year overall survival was 63%. We observed a 5-year survival in patients with level I-II 82% and level III and IV 46%.
Conclusions: Our results suggest the benefit for the patient of an aggressive surgical approach with an acceptable mortality and 5-year survival rate. The results obtained justify an aggressive surgical approach to these tumors.
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http://dx.doi.org/10.12865/CHSJ.47.01.15 | DOI Listing |
Viruses
November 2024
Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA 92093, USA.
In 2020, the in the county of San Diego (COSD) was launched, a private-public joint endeavor between the COSD and the American Liver Foundation. We use epidemic modeling to assess whether the COSD is on track to reach its elimination targets (80% reduction in incidence, 65% reduction in hepatitis C virus (HCV)-related mortality by 2030 compared to 2015) and what intervention scale-up may be required. We adapted a previously developed dynamic, deterministic model of HCV transmission and disease progression among adults in the COSD, stratified by risk, age, gender, and human immunodeficiency virus (HIV) status.
View Article and Find Full Text PDFPharmaceuticals (Basel)
November 2024
The Research Institute, The McGill University Health Center, Montreal, QC H4A 3J1, Canada.
Glioblastoma multiforme is an aggressive malignancy with a dismal 5-year survival rate of 5-10%. Current therapeutic options are limited, due in part to drug exclusion by the blood-brain barrier (BBB). We have previously shown that high-amplitude repetitive transcranial magnetic stimulation (rTMS) in rats allowed the delivery across the BBB of an IGF signaling inhibitor-IGF-Trap.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
HPV Research Laboratory, Department for Gynecology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
Head and neck squamous cell carcinoma (HNSCC) with discordant diagnostic patterns of HPV/p16 or HPV/p16 correlate with worse prognosis. This study aims to identify truly HPV-driven HNSCCs using a QuantiGene-Molecular-Profiling-Histology (QG-MPH) assay for identifying transcriptionally active HPV. Of 97 FFPE samples analyzed, 68 were valid for HPV DNA detection by PCR and quantification of HPV E7 and p16 mRNA by QG-MPH.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Istituto di Ricerca Pediatrica "Città della Speranza", 35128 Padua, Italy.
Currently, risk stratification for pediatric Hodgkin lymphoma is based on clinical factors such as stage, bulk, and systemic symptoms. Novel minimally invasive biomarkers could enhance both prognosis and treatment strategies. Therefore, the plasma extracellular vesicles' microRNA profile was characterized by small RNA sequencing in 36 classical Hodgkin lymphoma cases and these findings were confirmed in an extended cohort of 86 patients by RT-qPCR.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Department of Microbiology, Faculty of Medicine, Khon Kaen University, Mueang Khon Kaen, Khon Kaen 40002, Thailand.
Sinonasal squamous cell carcinoma (SNSCC) is a rare tumor with a high 5-year mortality rate. However, proteomic technologies have not yet been utilized to identify SNSCC-associated proteins, which could be used as biomarkers. In this study, we aimed to discover a biomarker to predict SNSCC patients using proteomic analysis integrated with machine learning models.
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