10123- COT-13 TREATMENT RESULTS OF TUMOR TREATING FIELD IN OUR HOSPITAL: EXAMINATION OF EARLY DROPOUT CAESE
Abstract BACKGROUND/PURPOSE Tumor treating field therapy (Novo-TTF) is a new treatment for glioblastoma that suppresses tumor growth by generating an alternating electric field in the brain. We have treated 21 cases since September 2019,and experienced a certain number of cases that dropped out of this treatment early. In this study, we examined TTF treatment at our hospital, with a particular focus on cases of early dropout. SUBJECTS/METHODS Nineteen patients with glioblastoma who underwent TTF at our hospital from September 2019 to July 2024 and were observed for at least 6 months. Patient information and outcome were analyzed retrospectively. RESULTS The median age of the patients was 64 years (33-72 years). Fourteen patients were males and five were females. The mean duration of TTF treatment was 9.9 months (0-55 months), and the mean usage rate was 41.0% (0-96.9%). Survival analyses showed that mPFS was 9 months and mOS was 23 months. Seven of 19 patients (37%) dropped out of treatment within 3 months (early dropout group). Compared to other patients (maintenance group), early dropout group included significantly more patients who had left cerebral lesions (71.4% vs. 16.7%, p=0.017) and fewer patients that KPS was 90 or higher (14.3% vs. 50.0%, p=0.144). Prognosis was significantly worse in the early dropout group compared to the maintenance group for both PFS and OS (p<0.01 for both PFS and OS), and multivariate analysis in PFS showed that early dropout was an independent poor prognostic factor (p=0.001). CONCLUSION In TTF treatment, the presence of patients who drop out early is a major factor that worsens the outcome of treatment. It is important to obtain the patient’s understanding and motivation for treatment in order to avoid early dropout. Tumor localization (left cerebellum) and low KPS may be potential disincentive factor for continue treatment.
Authors
- Fumitaka Matsumoto
- Shinji Yamashita (ORCID: https://orcid.org/0000-0001-5859-2828)
- Natsuki Ogasawara
- Mitsuru Tamura
- Yoshiko Okita (ORCID: https://orcid.org/0000-0002-2943-238X)
- Kiyotaka Yokogami (ORCID: https://orcid.org/0000-0003-1320-9383)
- Hironobu Okuyama
- Hajime Ohta (ORCID: https://orcid.org/0000-0001-5603-4443)
- Tomoki Kawano
Institutions
- University of Miyazaki (JP)
Publication Details
- Journal
- Neuro-Oncology Advances
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1093/noajnl/vdae173.102
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00