Treatment options for patients with metastatic renal cell carcinoma are limited. Interferon-alpha has an overall response rate of 10-15% in phase II and III clinical trials and is considered a standard option for patients. Though the anti-estrogen toremifene has shown only modest single agent activity in renal cell carcinoma, evidence for synergy of anti-estrogens with interferon-alpha exists in renal cell and other cancers. Therefore, a phase II trial was undertaken to test the combination of interferon-alpha and toremifene in advanced renal cell carcinoma. Thirteen patients with measurable metastatic or unresectable local disease were treated with interferon-alpha at a dose of 5 million units/m2 three times a week and daily oral toremifene at 300 mg daily in divided doses. Patients were treated for 12 weeks and then restaged. Clinical response was the primary endpoint of the trial. Four patients (31%) had evidence of stable disease at 12 weeks, while the remaining nine patients (69%) progressed on treatment. Toxicity was moderate, with grade 2 or 3 fatigue, nausea and anorexia each noted in 31% of patients. We conclude that the combination of interferon-alpha plus toremifene demonstrates no significant activity in advanced renal cell carcinoma.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1081/cnv-120001145 | DOI Listing |
Indian J Urol
January 2025
Department of Urology, Cancer Institute of the State of São Paulo, São Paulo, Brazil.
Purpose: This study aims to assess the impact of unclassified renal cell carcinoma (uRCC) on clinical, pathological, and oncological outcomes compared with clear cell renal cell carcinoma (ccRCC).
Materials And Methods: We analyzed the data of 48 uRCC and 688 ccRCC cases, collected from a histopathological database at a single center from July 2011 to August 2019. uRCC cases were confirmed according to the 2016 World Health Organization classification.
Int J Nanomedicine
January 2025
School of Pharmacy, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Purpose: To improve the oral absorption of relugolix (RLGL), which has low oral bioavailability due to its low solubility and being a substrate of P-glycoprotein (P-gp). A solid self-microemulsifying drug delivery system of relugolix (RLGL-S-SMEDDS) was prepared and evaluated in vitro and in vivo.
Methods: The composition of the solid self-microemulsifying drug delivery system (S-SMEDDS) was selected by solubility study and pseudo-ternary phase diagram, and further optimized by Design-Expert optimization design.
Biochem Biophys Rep
December 2024
Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Background: Renal cell carcinoma (RCC) is a common urological cancer globally and shows a favorable prognosis in early stages of the tumor progression. Due to the poor prognosis for metastatic RCC patients, it is crucial to explore the molecular biology of RCC progression to establish efficient diagnostic and therapeutic markers for these patients. Long non-coding RNAs (lncRNAs) have critical roles in regulation of tumor cell proliferation, migration, and apoptosis during RCC progression.
View Article and Find Full Text PDFJACC Asia
January 2025
Division of Cardiology, Department of Internal Medicine, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Background: Patients with end-stage renal disease (ESRD) are at a higher risk of cardiovascular diseases. Intravascular imaging (IVI)-guided percutaneous coronary intervention (PCI) using optical coherence tomography (OCT) or intravascular ultrasound (IVUS) has been shown to result in better clinical outcomes than angiography guidance. Nevertheless, the clinical outcomes of IVI-guided PCI in ESRD patients remain uncertain.
View Article and Find Full Text PDFBMJ Oncol
November 2024
Department of Computer Science, Durham University, Durham, UK.
Objectives: Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!