Anne Line Stensjøen1, Erik Magnus Berntsen2, Vilde E Mikkelsen3, Sverre H Torp4, Asgeir S Jakola5, Øyvind Salvesen6, Ole Solheim7. 1. Department of Circulation and Medical Imaging, Faculty of Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology, St. Olav's University Hospital, Trondheim, Norway. Electronic address: alinesten@gmail.com. 2. Department of Circulation and Medical Imaging, Faculty of Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology, St. Olav's University Hospital, Trondheim, Norway. 3. Department of Laboratory Medicine, Children's and Women's Health, Faculty of Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway. 4. Department of Laboratory Medicine, Children's and Women's Health, Faculty of Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway; Department of Pathology and Medical Genetics, St. Olav's University Hospital, Trondheim, Norway. 5. Department of Neurosurgery, St. Olav's University Hospital, Trondheim, Norway; Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden; Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden. 6. Department of Public Health and General Practice, Faculty of Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway. 7. Department of Neuroscience, Faculty of Medicine, NTNU-Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurosurgery, St. Olav's University Hospital, Trondheim, Norway; National Competence Centre for Ultrasound and Image Guided Therapy, St. Olav's University Hospital, Trondheim, Norway.
Abstract
BACKGROUND: Glioblastomas are highly aggressive and heterogeneous tumors, both in terms of patient outcome and molecular profile. Magnetic resonance imaging of tumor growth could potentially reveal new insights about tumor biology noninvasively. The aim of this exploratory retrospective study was to investigate the prognostic potential of pretreatment growth rate of glioblastomas, after controlling for known prognostic factors. METHODS: A growth model derived from clinical pretreatment postcontrast T1-weighted magnetic resonance imaging images was used to divide 106 glioblastoma patients into 2 groups. The "faster growth" group had tumors growing faster than expected based on their volume at diagnosis, whereas the "slower growth" group had tumors growing slower than expected. Associations between tumor growth and survival were examined by the use of multivariable Cox regression and logistic regression. RESULTS: None of the known prognostic factors were significantly associated with tumor growth. An extended multivariable Cox model showed that during the first 12 months of follow-up, there was no significant difference in survival between faster and slower growing tumors. Beyond 12 months' follow-up, however, there was a significant, independent survival benefit in having a tumor with slower pretreatment growth. In a multiple logistic regression model including patients receiving both radiotherapy and chemotherapy (n = 82), slower pre-treatment growth of the tumor was shown to be a significant predictor of 2-year survival (odds ratio 4.4). CONCLUSIONS: Pretreatment glioblastoma growth harbors prognostic information. Patients with slower growing tumors have higher odds of survival beyond 2 years, adjusted for other prognostic factors.
BACKGROUND:Glioblastomas are highly aggressive and heterogeneous tumors, both in terms of patient outcome and molecular profile. Magnetic resonance imaging of tumor growth could potentially reveal new insights about tumor biology noninvasively. The aim of this exploratory retrospective study was to investigate the prognostic potential of pretreatment growth rate of glioblastomas, after controlling for known prognostic factors. METHODS: A growth model derived from clinical pretreatment postcontrast T1-weighted magnetic resonance imaging images was used to divide 106 glioblastomapatients into 2 groups. The "faster growth" group had tumors growing faster than expected based on their volume at diagnosis, whereas the "slower growth" group had tumors growing slower than expected. Associations between tumor growth and survival were examined by the use of multivariable Cox regression and logistic regression. RESULTS: None of the known prognostic factors were significantly associated with tumor growth. An extended multivariable Cox model showed that during the first 12 months of follow-up, there was no significant difference in survival between faster and slower growing tumors. Beyond 12 months' follow-up, however, there was a significant, independent survival benefit in having a tumor with slower pretreatment growth. In a multiple logistic regression model including patients receiving both radiotherapy and chemotherapy (n = 82), slower pre-treatment growth of the tumor was shown to be a significant predictor of 2-year survival (odds ratio 4.4). CONCLUSIONS: Pretreatment glioblastoma growth harbors prognostic information. Patients with slower growing tumors have higher odds of survival beyond 2 years, adjusted for other prognostic factors.
Authors: Even Hovig Fyllingen; Lars Eirik Bø; Ingerid Reinertsen; Asgeir Store Jakola; Lisa Millgård Sagberg; Erik Magnus Berntsen; Øyvind Salvesen; Ole Solheim Journal: Acta Neurochir (Wien) Date: 2021-03-20 Impact factor: 2.216
Authors: Vilde Elisabeth Mikkelsen; Anne Line Stensjøen; Unn Sophie Granli; Erik Magnus Berntsen; Øyvind Salvesen; Ole Solheim; Sverre Helge Torp Journal: BMC Cancer Date: 2018-09-03 Impact factor: 4.430