Adaptive Radiotherapy for Glioblastoma Multiforme – The Impact on Disease Outcome

Végváry, Zoltán; Darázs, Barbara; Paczona, Viktor; Dobi, Ágnes; Reisz, Zita; Varga, Zoltán; Fodor, Emese; Cserháti, Adrienn; Oláh, Judit; Kis, Dávid; Barzó, Pál; Hidéghety, Katalin

doi:10.21873/anticanres.14425

Cited by 7 publications

(5 citation statements)

References 38 publications

(50 reference statements)

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“…The majority of patients with grade III or IV gliomas and selected patients with grade II gliomas are scheduled for radiochemotherapy, mainly following neurosurgical resection (4)(5)(6). This situation may produce significant emotional distress for the patients due to fears regarding the treatment procedure, potential side effects, and unsatisfactory treatment outcomes including progression or recurrence of the glioma (7)(8)(9)(10)(17)(18)(19). These fears may lead to sleep problems that can significantly impair the patients' quality of life (11)(12)(13).…”

Section: Discussionmentioning

confidence: 99%

Risk Factors for Sleep Problems Prior to Radiochemotherapy for Malignant Gliomas

Kopelke

Kjær

Tvilsted

et al. 2021

In Vivo

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Background/Aim: Many patients with malignant gliomas are scheduled for radiochemotherapy, which may cause emotional distress associated with sleep problems. This study aimed to determine the prevalence of such sleep problems in these patients and identify risk factors. Patients and Methods: Fifty-seven patients scheduled for radiochemotherapy for grade II-IV gliomas were retrospectively investigated for pre-treatment sleep problems. Fifteen characteristics were evaluated including temporal relation to age, gender, performance status, comorbidity, (family) history of malignancies, distress score, emotional problems, physical problems, practical problems, involved sites, glioma grade, upfront surgery, and corticosteroids. Results: Nineteen patients stated pre-treatment sleep problems (prevalence=66.7%). Significant associations with sleep problems were found for female gender (p=0.023), presence of emotional problems (p=0.006), and ≥4 physical problems (p<0.001). A trend was found for distress scores ≥5 (p=0.077). Conclusion: The prevalence of sleep problems was high. Risk factors were determined that can be used to identify patients who likely benefit from psychological support.According to the classification of the World Health Organization (WHO), the group of gliomas includes four grades (grades I to IV), of which grade IV tumors (glioblastoma multiforme) are the most aggressive lesions with a 5-year survival rate of about 5% (1-3).Neurosurgical resection should be performed whenever safely possible. In patients with grade III or IV gliomas, resection is generally followed by radiochemotherapy (4-6). This applies also to selected patients with grade II gliomas, mainly after incomplete resection. Assignment to a course of radiochemotherapy may cause significant distress for the patients who may be afraid particularly of the exposure to radiation and potential treatment-related adverse events (7-10). The distress may lead to sleep problems that can significantly impair the patients' quality of life and require psychological support already prior to the start of radiochemotherapy (11)(12)(13). Therefore, the present study investigated the prevalence and potential risk factors of pre-treatment sleep problems in patients with grade II to IV gliomas assigned to radiochemotherapy. These data can contribute to the identification of patients who would likely benefit from psychological support beginning already prior to their course of radiochemotherapy. Patients and MethodsIn this retrospective study, 57 patients scheduled for radiochemotherapy of WHO grade II-IV gliomas were investigated with respect to pre-treatment sleep problems. These patients had completed the National Comprehensive Cancer Network (NCCN) Distress Thermometer (14,15) between February 2019 and March 2021. The study was approved as a part of a larger project by the Ethics Committee of the University of Lübeck (reference 21-284). The technique to be used for the planned radiotherapy was volumetricmodulated arc therapy (VMAT). The preferred dose-frac...

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Section: Discussionmentioning

confidence: 99%

Risk Factors for Sleep Problems Prior to Radiochemotherapy for Malignant Gliomas

Kopelke

Kjær

Tvilsted

et al. 2021

In Vivo

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“…Our observations support the previous notions that locally and distally recurrent glioblastomas exhibit different evolutionary patterns, in particular, linear and branching evolutions, respectively, and that the location of tumor recurrence helps predict the evolutionary pattern in glioblastoma. Concurrent chemoradiation therapy exerts a powerful selective pressure, and chemo-and radio-resistant cell clones contribute to the development of glioblastoma recurrence (7,(40)(41)(42)(43)(44). Common ancestral cells are likely to pre-exist in the untreated primary glioblastoma and are positively selected by chemoradiation therapy (18,41,(45)(46)(47).…”

Section: Discussionmentioning

confidence: 99%

Targeted Genomic Sequencing Reveals Different Evolutionary Patterns Between Locally and Distally Recurrent Glioblastomas

Yoon

Kim

Lee

et al. 2020

Cancer Genomics Proteomics

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Background/Aim: Glioblastoma is the most malignant form of astrocytoma. The purpose of this study was to analyze the genetic characteristics of primary and recurrent glioblastomas using targeted sequencing and investigate the differences in mutational profiles between the locations of tumor recurrence. Materials and Methods: Fourteen glioblastoma patients who developed local (n=10) or distal (n=4) recurrence were included in the study. Targeted sequencing analysis was performed using the primary (n=14) and corresponding recurrent (n=14) tumor tissue samples. Results: The local and distal recurrence groups showed different genetic evolutionary patterns. Most of the locally recurrent glioblastomas demonstrated concordant mutational profiles between the primary and recurrent tumors, suggesting a linear evolution. In contrast, all cases of distally recurrent glioblastomas showed changes in mutational profiles with newly acquired mutations when compared to the corresponding primary tumors, suggesting a branching evolution. Conclusion: Locally and distally recurrent glioblastomas exhibit different evolutionary patterns. Glioblastoma is the most common malignant tumor of the central nervous system (1-9). The current standard treatment for glioblastoma involves surgical resection, followed by concurrent chemoradiation therapy and adjuvant chemotherapy using temozolomide (8-12). Due to the invasive nature of glioblastoma, surgical resection rarely eliminates all tumor cells, and postoperative treatment is usually necessary to prevent disease recurrence. Despite the advances made in therapeutic strategies, the prognosis of patients with glioblastoma remains very poor, with an average survival of 15 months (13-15) and disease recurrence being the major cause of mortality (16-18). Recurrent glioblastomas tend to be more invasive and resistant to chemotherapy than primary tumors. An understanding of the genetic characteristics of recurrent glioblastoma is crucial for identifying potential targets for drug discovery, stratifying patients for diagnosis, and optimizing an effective treatment strategy. Previous studies have shown the molecular features of recurrent glioblastomas. In particular, the mutational profiles observed in recurrent glioblastomas were compared to those of the corresponding primary tumors (19-21). However, there is a lack of studies exploring the differences in mutational profiles between recurrent glioblastomas at different sites (21, 22). In this study, we investigated the mutational profiles of primary and recurrent glioblastomas using 803 This article is freely accessible online.

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“…Further research found that (1) during the implementation of ART technology, the degree of changes in tumor regression is closely related to the dose range of the irradiation target area and the irradiation dose of adjacent normal tissues and organs [7]. (2) e degree of tumor regression varies among patients during treatment, and some patients have no significant changes in tumor volume during the pre-course and mid-course treatment (possibly due to radiation resistance) [8]. In view of this, some scholars believe that these patients may not benefit from ART, and may not need ART at least in the first and middle course of treatment.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Prediction of Changes in Tumor Regression during Radiotherapy for Nasopharyngeal Carcinoma by Using the Computed Tomography‐Based Radiomics

Yang

Mai

et al. 2022

Contrast Media & Molecular Imaging

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This work aimed to explore the application value of computed tomography (CT)-based radiomics in predicting changes in tumor regression during radiotherapy for nasopharyngeal carcinoma. In this work, 144 patients with nasopharyngeal carcinoma who underwent concurrent chemoradiotherapy (CCRT) in our hospital from January 2015 to December 2021 were selected. The patients were divided into a radiosensitive group (79 cases) and an insensitive group (65 cases) according to the tumor volume shrinkage during radiotherapy. The 3D Slicer 4.10.2 software was used to delineate the tumor region of interest (ROI), and a total of 1223 radiomics features were extracted using the radiomics module under the software. After between-group and within-group consistency tests, one-way ANOVA, and LASSO dimensionality reduction, three omics features were finally selected for the establishment of predictive models. At the same time, the age, gender, tumor T stage and N stage, hemoglobin, and albumin of the patients were collected to establish a clinical prediction model. The results showed that compared with logistic regression, decision tree, random forest, and AdaBoost models, the SVM model based on CT radiomics features had the best performance in predicting tumor regression changes during tumor radiotherapy (training group area under the receiver operating characteristic curve (AUC): 0.840 (95% confidence interval (CI): 0.764–0.916); validation group: AUC: 0.810 (95% CI: 0.676–0.944)). Compared with the supported vector machine (SVM) prediction model based on clinical features, the SVM model based on radiomics features had better performance in predicting the change of retraction during tumor radiotherapy (training group: omics feature SVM model AUC: 0.84, clinical feature SVM model: 0.78; validation group: omics feature SVM model AUC: 0.8, clinical feature SVM model: 0.58, P = 0.044). Based on the radiomics characteristics and clinical characteristics of patients, a nomo prediction map was established, and the calibration curve shows good consistency, which can be visualized to assist clinical judgment. In this work, the prediction model composed of CT-based radiomic features combined with clinical features can accurately predict withdrawal changes during tumor radiotherapy, ensuring the accuracy of treatment planning, and minimizing the number of CT scans during radiotherapy.

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Adaptive Radiotherapy for Glioblastoma Multiforme – The Impact on Disease Outcome

Cited by 7 publications

References 38 publications

Risk Factors for Sleep Problems Prior to Radiochemotherapy for Malignant Gliomas

Risk Factors for Sleep Problems Prior to Radiochemotherapy for Malignant Gliomas

Targeted Genomic Sequencing Reveals Different Evolutionary Patterns Between Locally and Distally Recurrent Glioblastomas

[Retracted] Prediction of Changes in Tumor Regression during Radiotherapy for Nasopharyngeal Carcinoma by Using the Computed Tomography‐Based Radiomics

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