Purpose: Patients with advanced non-small-cell lung cancer (NSCLC) have a short life expectancy; therefore, in addition to increasing their survival, improving their quality of life (QoL) is also an important treatment goal.
Methods: We evaluated the QoL of patients with advanced NSCLC who were unfit to receive chemotherapy, failed to respond or progress following prior chemotherapy, who received subsequent treatment with gefitinib ('Iressa') on a compassionate use basis, using a standard QoL questionnaire, (EORTC) QLQ-C30 and the related lung cancer-specific module QLQ-LC13.
Results: Analysis of the functional scales showed a trend towards improvement for role, emotional and cognitive scales, while a substantial stability was seen for general QoL scale. Analysis of the symptoms scales of QLQ-C30, showed a trend towards improvement for fatigue, dyspnoea, insomnia, and constipation, after one month of therapy. Fifty-six of the 57 patients were considered evaluable for response. One patient evidenced a partial response (patient is still on response), 29 patients had stable disease for a median duration of 5 months (range 4-7 months), and 26 patients progressed.
Conclusions: After treatment with Gefitinib, we observed maintenance of QoL in a group of patients with poor prognosis that would be expected to have a worsening QoL. Furthermore important symptoms like dyspnoea fatigue and pain in other parts, that usually afflict patients with NSCLC, showed a trend toward improvement after only one month of therapy.
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Sci Rep
December 2024
Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.
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December 2024
Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Canada.
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.
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December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
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December 2024
Department of Orthopedic Surgery, Arthroscopy and Joint Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
The humeral head is the second most common anatomical site of osteonecrosis after the femoral head. Studies have reported satisfactory clinical outcomes after shoulder arthroplasty to treat osteonecrosis of the humeral head (ONHH). However, there are concerns regarding implant longevity in relatively young patients.
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December 2024
Institute of Pathology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Pathogenic activating mutations in the fibroblast growth factor receptor 3 (FGFR3) drive disease maintenance and progression in urothelial cancer. 10-15% of muscle-invasive and metastatic urothelial cancer (MIBC/mUC) are FGFR3-mutant. Selective targeting of FGFR3 hotspot mutations with tyrosine kinase inhibitors (e.
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