Background And Purpose: To assess treatment outcome and prognostic factors following postoperative external radiotherapy in 77 patients with low-grade glioma.
Patients And Methods: Between 1977 and 1996, 45 patients with astrocytoma, 14 with oligodendroglioma and 18 with mixed glioma received postoperative radiotherapy with a median total dose of 52 Gy (range, 45 to 61 Gy). Sixty-seven patients were treated immediately following surgery, 10 patients with tumor progression. The influence of various factors including histology, gender, age, seizures, duration of symptoms (< or = 6 weeks vs > 6 weeks), CT pattern (enhancement vs no enhancement), type of surgery, total radiotherapy dose and timing of radiotherapy on relapse-free survival and overall survival was investigated.
Results: The median overall survival time was 81 months, the 5- and 10-year survival rates were 54% and 31%, respectively. The median time to progression was 56 months, while the 5- and 10-year progression-free survival rates were 45% and 24%. Univariate analyses identified the total radiotherapy dose (p = 0.01), duration of symptoms (p = 0.05), the presence of seizures (p = 0.04), and the CT pattern following intravenous contrast (p = 0.005) as significant prognostic factors for overall survival. Progression-free survival rates were influenced by the total dose (p = 0.04), the duration of symptoms (p = 0.01) and CT pattern (p = 0.006). On multivariate analysis, only the CT pattern (enhancement vs no enhancement) remained as independent prognostic factors for both progression-free survival and overall survival.
Conclusions: A minimum total dose of 52 Gy is recommended for the postoperative radiotherapy in low-grade glioma. Tumors with CT enhancement seem to need further intensification of treatment.
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http://dx.doi.org/10.1007/s000660050007 | DOI Listing |
Postgrad Med J
January 2025
Department of Pediatric Metabolic Diseases, University of Health Sciences, Ankara Etlik City Hospital, Ankara 06170, Turkey.
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January 2025
Qingshan Lake Science and Technology Innovation Center, Hangzhou Medical College, Hangzhou, China.
Background: Ischemic stroke is a prevalent and life-threatening cerebrovascular disease that is challenging to treat and associated with a poor prognosis. Astragaloside IV (AS-IV), a primary bioactive component of Astragali radix, has demonstrated neuroprotective benefits in previous studies. This study aimed to explore the mechanisms through which AS-IV may treat cerebral ischemia-reperfusion injury (CIRI).
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R Madhavan Nayar Center for Comprehensive Epilepsy Care, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India.
Background: The role of imaging in autoimmune encephalitis (AIE) remains unclear, and there are limited data on the utility of magnetic resonance imaging (MRI) to diagnose, treat, or prognosticate AIE.
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Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFHum Reprod Open
November 2024
Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?
Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.
What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.
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