Frontiers in oncology
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Frontiers in oncology · Jan 2019
The Impact of Formal Mentorship Programs on Mentorship Experience Among Radiation Oncology Residents From the Northeast.
Purpose: Strong mentorship has been shown to improve mentee productivity, clinical skills, medical knowledge, and career preparation. We conducted a survey to evaluate resident satisfaction with mentorship within their radiation oncology residency programs. Methods and Materials: In January 2019, 126 radiation oncology residents training at programs in the northeastern United States were asked to anonymously complete the validated Munich Evaluation of Mentoring Questionnaire (MEMeQ). ⋯ Overall, 38% of residents were either satisfied/very satisfied with their mentoring experience, while 49% of residents were unsatisfied/very unsatisfied. Conclusion: Residents participating in a formal mentorship program are significantly more likely to be satisfied with their mentoring experience than those who are not. Our results suggest that radiation oncology residency programs should strongly consider implementing formal mentorship programs.
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Frontiers in oncology · Jan 2019
Evaluation of Lymph Node Metastasis in Advanced Gastric Cancer Using Magnetic Resonance Imaging-Based Radiomics.
Objective: To develop and evaluate a diffusion-weighted imaging (DWI)-based radiomic nomogram for lymph node metastasis (LNM) prediction in advanced gastric cancer (AGC) patients. Overall Study: This retrospective study was conducted with 146 consecutively included pathologically confirmed AGC patients from two centers. All patients underwent preoperative 3.0 T magnetic resonance imaging (MRI) examination. ⋯ Meanwhile, the specificity, sensitivity, and accuracy were 0.846, 0.853, and 0.851 in internal validation cohort, and 0.714, 0.952, and 0.893 in external validation cohort, compensating for the MRI-reported N staging and MRI-derived model. DCA demonstrated good clinical use of radiomic nomogram. Conclusions: This study put forward a DWI-based radiomic nomogram incorporating the radiomic signature, minimum ADC, and MRI-reported N staging for individualized preoperative detection of LNM in patients with AGC.
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Frontiers in oncology · Jan 2019
Ability of Radiomics in Differentiation of Anaplastic Oligodendroglioma From Atypical Low-Grade Oligodendroglioma Using Machine-Learning Approach.
Objectives: To investigate the ability of radiomics features from MRI in differentiating anaplastic oligodendroglioma (AO) from atypical low-grade oligodendroglioma using machine-learning algorithms. Methods: A total number of 101 qualified patients (50 participants with AO and 51 with atypical low-grade oligodendroglioma) were enrolled in this retrospective, single-center study. Forty radiomics features of tumor images derived from six matrices were extracted from contrast-enhanced T1-weighted (T1C) images and fluid-attenuation inversion recovery (FLAIR) images. ⋯ For models based on T1C images, the combination of LASSO and RF classifier represented the highest AUC of 0.904 in the validation group. For models based on FLAIR images, the combination of GBDT and RF classifier showed the highest AUC of 0.861 in the validation group. Conclusion: Radiomics-based machine-learning approach could potentially serve as a feasible method in distinguishing AO from atypical low-grade oligodendroglioma.
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Frontiers in oncology · Jan 2019
Publication Landscape Analysis on Gliomas: How Much Has Been Done in the Past 25 Years?
Introduction: The body of glioma-related literature has grown significantly over the past 25 years. Despite this growth in the amount of published research, gliomas remain one of the most intransigent cancers. The purpose of this study was to analyze the landscape of glioma-related research over the past 25 years using machine learning and text analysis. ⋯ The current research landscape covers clinical, pre-clinical, biological, and technical aspects of glioblastoma; at present, researchers appear to be less concerned with glioblastoma's psychological effects or patients' end-of-life care. Conclusion: Publication of glioma-related research has expanded rapidly over the past 25 years. Common topics include the disease's molecular background, patients' survival, and treatment outcomes; more research needs to be done on the psychological aspects of glioblastoma and end-of-life care.
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Frontiers in oncology · Jan 2019
Prognostic Role of Platelet-to-Lymphocyte Ratio in Patients With Bladder Cancer: A Meta-Analysis.
Background: Many studies have been reported that platelet-to-lymphocyte ratio (PLR) may be associated with the prognosis of bladder cancer, but the results are inconsistent. Therefore, we performed a meta-analysis to evaluate the effect of pretreatment PLR on the prognosis of bladder cancer. Methods: The databases PubMed, Embase, Cochrane Library, and Web of Science were searched. ⋯ An elevated PLR was significantly associated with poorer overall survival (OS) (HR = 1.26, 95% CI = 1.03-1.54, p = 0.026), but not with cancer-specific survival (CSS) (HR = 1.15, 95% CI = 0.95-1.38, p = 0.149), or recurrence-free survival (RFS) (HR = 1.72, 95% CI = 0.79-3.75, p = 0.175). In addition, high PLR was correlated with age ≥ 65 years (OR = 1.82, 95% CI = 1.24-2.67, p = 0.002), whereas was not significantly correlated with sex, tumor grade, tumor stage, distant metastasis, or tumor size. Conclusions: The pretreatment PLR could serve as a predicative biomarker of poor prognosis for patients with bladder cancer.