scholarly journals The Impact of Adjuvant Radiation Therapy and Elective Nodal Irradiation in Early Stage/Low Grade versus Advanced Stage/High Grade Olfactory Neuroblastoma

2018 ◽  
Vol 102 (3) ◽  
pp. e360-e361 ◽  
Author(s):  
A.R. Wolfe ◽  
B. Klamer ◽  
J. Pan ◽  
D. Prevedello ◽  
A.D. Bhatt ◽  
...  
Keyword(s):  
Early Stage ◽  
Olfactory Neuroblastoma ◽  
Adjuvant Radiation ◽  
Low Grade ◽  
High Grade ◽  
Advanced Stage ◽  
Elective Nodal Irradiation ◽  
Adjuvant Radiation Therapy ◽  
Grade Versus ◽  
The Impact

Aggressive Salivary Malignancies at Early Stage: Outcomes and Implications for Treatment

2017 ◽  
Vol 126 (7) ◽  
pp. 525-529 ◽  
Author(s):  
Robert W. Eppsteiner ◽  
Jonathan W. Fowlkes ◽  
Carryn M. Anderson ◽  
Robert A. Robinson ◽  
Nitin A. Pagedar
Keyword(s):  
Radiation Therapy ◽  
Early Stage ◽  
Relative Survival ◽  
Carcinoma Ex Pleomorphic Adenoma ◽  
Adjuvant Radiation ◽  
Major Salivary Gland ◽  
High Grade ◽  
Duct Carcinoma ◽  
The Impact ◽  
Case Basis

Background: Few studies have examined whether the use of adjuvant treatment impacts survival for early stage high-grade salivary tumors. Methods: A retrospective review of the SEER database between 1973 and 2012 was performed. Patients with high-grade major salivary gland tumors including salivary duct carcinoma, carcinoma ex-pleomorphic adenoma, high-grade mucoepidermoid carcinoma, or adenocarcinoma, NOS were identified. Only stage I-II tumors were included. The impact of radiation status on observed and relative survival was examined. Results: Five hundred seventy-four patients with high-grade, early stage salivary tumors met inclusion criteria. Sixty-seven percent of patients received radiation therapy. There was no difference in observed or relative survival based on having received radiation. Conclusions: Adjuvant radiation is indicated for advanced stage tumors or early stage tumors with adverse features. For early stage tumors without adverse features, there was no survival benefit from radiation therapy. Adjuvant radiation should be decided on a case-by-case basis for these patients.

The Impact of Adjuvant Radiation Therapy for High-Grade Gliomas by Histology in the United States Population

2014 ◽  
Vol 90 (4) ◽  
pp. 894-902 ◽  
Author(s):  
Chad G. Rusthoven ◽  
Julie A. Carlson ◽  
Timothy V. Waxweiler ◽  
Miranda J. Dally ◽  
Anna E. Barón ◽  
...  
Keyword(s):  
United States ◽  
Radiation Therapy ◽  
The United States ◽  
Adjuvant Radiation ◽  
High Grade ◽  
Adjuvant Radiation Therapy ◽  
United States Population ◽  
High Grade Gliomas ◽  
The Impact

scholarly journals Regional Recurrences and Hyams Grade in Esthesioneuroblastoma

2020 ◽  
Author(s):  
Hedyeh Ziai ◽  
Eugene Yu ◽  
Ilan Weinreb ◽  
Bayardo Perez-Ordonez ◽  
Christopher M. K. L. Yao ◽  
...  
Keyword(s):  
Overall Survival ◽  
Small Sample Size ◽  
Tertiary Care ◽  
Small Sample ◽  
Oncologic Outcomes ◽  
Low Grade ◽  
High Grade ◽  
Grade Versus ◽  
Regional Failure ◽  
The Impact

Abstract Objective The aim of this study is to determine if Hyams grade may help predict which patients with esthesioneuroblastoma (ENB) tumors are likely to develop regional recurrences, and to determine the impact of tumor extent on regional failure in ENB patients without evidence of nodal disease at presentation. Design The study was designed as a retrospective review for ENB patients. Settings The study was prepared at tertiary care academic center for ENB patients. Participants Patients with ENB were included in the study. Main Outcome Measures  Oncologic outcomes (5-year regional and locoregional control (LRC) and overall survival) in patients with Hyams low grade versus high grade. Oncologic outcomes based on radiographic disease extent. Results A total of 43 patients were included. Total 25 patients (58%) had Hyams low-grade tumor, and 18 (42%) had high-grade tumor. Of the 34 patients without regional disease at presentation, 8 (24%) were treated with elective nodal radiation. There were no statistically significant differences in 5-year regional control in the Hyams low-grade versus high-grade groups (78 vs. 89%; p = 0.4). The 5-year LRC rates in patients with low grade versus high grade were 73 versus 89% (p = 0.6). The 5-year overall survival rates in patients with low-grade versus high-grade tumors were 86 versus 63% (p = 0.1). Radiographic extension of disease into the olfactory groove, olfactory nerve, dura, and periorbita were statistically associated with decreased 5-year overall survival (5-year OS 49 vs. 91% [p = 0.04], 49 vs. 91% [p = 0.04], 44 vs. 92% [p = 0.02], and 44 vs. 80% [p = 0.04], respectively). Conclusion ENBs are associated with a risk of regional failure. The current analysis suggests that Hyams low-grade and high-grade malignancies have comparable rates of early and delayed regional recurrences, although small sample size may limit our conclusions.

scholarly journals Impact of Pathological Stratification on the Clinical Outcomes of Advanced Well-Differentiated/Dedifferentiated Liposarcoma Treated with Trabectedin

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1453
Author(s):  
Chiara Fabbroni ◽  
Giovanni Fucà ◽  
Francesca Ligorio ◽  
Elena Fumagalli ◽  
Marta Barisella ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Proportional Hazards ◽  
Case Series ◽  
Progression Free Survival ◽  
Cox Proportional Hazards ◽  
Low Grade ◽  
High Grade ◽  
Retrospective Case ◽  
Well Differentiated ◽  
The Impact

Background. We previously showed that grading can prognosticate the outcome of retroperitoneal liposarcoma (LPS). In the present study, we aimed to explore the impact of pathological stratification using grading on the clinical outcomes of patients with advanced well-differentiated LPS (WDLPS) and dedifferentiated LPS (DDLPS) treated with trabectedin. Patients: We included patients with advanced WDLPS and DDLPS treated with trabectedin at the Fondazione IRCCS Istituto Nazionale dei Tumori between April 2003 and November 2019. Tumors were categorized in WDLPS, low-grade DDLPS, and high-grade DDLPS according to the 2020 WHO classification. Patients were divided in two cohorts: Low-grade (WDLPS/low-grade DDLPS) and high-grade (high-grade DDLPS). Results: A total of 49 patients were included: 17 (35%) in the low-grade cohort and 32 (65%) in the high-grade cohort. Response rate was 47% in the low-grade cohort versus 9.4% in the high-grade cohort (logistic regression p = 0.006). Median progression-free survival (PFS) was 13.7 months in the low-grade cohort and 3.2 months in the high-grade cohort. Grading was confirmed as an independent predictor of PFS in the Cox proportional-hazards regression multivariable model (adjusted hazard ratio low-grade vs. high-grade: 0.45, 95% confidence interval: 0.22–0.94; adjusted p = 0.035). Conclusions: In this retrospective case series, sensitivity to trabectedin was higher in WDLPS/low-grade DDLPS than in high-grade DDLPS. If confirmed in larger series, grading could represent an effective tool to personalize the treatment with trabectedin in patients with advanced LPS.

scholarly journals Low and high grade glioma segmentation in multispectral brain MRI data

2018 ◽  
Vol 10 (1) ◽  
pp. 110-132 ◽  
Author(s):  
László Szilágyi ◽  
David Iclănzan ◽  
Zoltán Kapás ◽  
Zsófia Szabó ◽  
Ágnes Győrfi ◽  
...  
Keyword(s):  
Early Stage ◽  
Brain Mri ◽  
High Grade Glioma ◽  
Detection Algorithm ◽  
Gabor Wavelet ◽  
Low Grade ◽  
Data Sets ◽  
Morphological Operations ◽  
High Grade ◽  
Mass Screening System

Abstract Several hundreds of thousand humans are diagnosed with brain cancer every year, and the majority dies within the next two years. The chances of survival could be easiest improved by early diagnosis. This is why there is a strong need for reliable algorithms that can detect the presence of gliomas in their early stage. While an automatic tumor detection algorithm can support a mass screening system, the precise segmentation of the tumor can assist medical staff at therapy planning and patient monitoring. This paper presents a random forest based procedure trained to segment gliomas in multispectral volumetric MRI records. Beside the four observed features, the proposed solution uses 100 further features extracted via morphological operations and Gabor wavelet filtering. A neighborhood-based post-processing was designed to regularize and improve the output of the classifier. The proposed algorithm was trained and tested separately with the 54 low-grade and 220 high-grade tumor volumes of the MICCAI BRATS 2016 training database. For both data sets, the achieved accuracy is characterized by an overall mean Dice score > 83%, sensitivity > 85%, and specificity > 98%. The proposed method is likely to detect all gliomas larger than 10 mL.

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