An Investigation of Cognitive Deficits Related to Surgery for Glioblastoma using a Computerised Assessment Tool
Thesis Abstract An Investigation of Cognitive Deficits Related to Surgery for Glioblastoma using a Computerised Assessment Tool - Rohitashwa Sinha Glioblastoma, the most aggressive type of primary brain cancer, causes abysmal survival rates and high risks of cognitive deficit to its sufferers. These deficits are due to both its being diffusely infiltrative and its radical treatments such as brain surgery and radiotherapy. Currently the course of cognitive deficits from before to after surgery has not been reliably researched. Studies report high rates of drop-out due to burdensome ‘pen-and-paper’ based assessments conducted by neuropsychologists, a lack of these resources entirely or the data collection being focused on the period around radiotherapy or less aggressive tumours instead. As a result, patients still undergo resection surgery for glioblastoma without a reliable evidence base for making their treatment decisions, without any assessment for their cognitive deficit burden and without any targeted interventions to protect their cognitive function. In this doctoral research, I have set up a prospective study to assess cognitive function before and after resection surgery, but before radiotherapy and with particular focus on participants with glioblastoma who have been underserved by current infrastructure and research focus. The methodology involves using a computerised testing battery called ‘OCS-Bridge’, which has broadened the access to such cognitive assessments. Participant retention has been higher than in the literature. This may be due in part to the efficiency of the format as well as the study design for data collection, where assessment timepoints were advised by patients and carers rather than clinicians. Using a variety of analysis techniques, this thesis progresses through a systematic review confirming the lack of reliable consensus in this area and a format comparison study to support the use of OCS-Bridge by comparison to conventional testing. Next, machine learning and Kaplan-Meier analyses are used to show cognitive deficits as predictors of clinical outcomes including overall survival. The longitudinal analyses of the high peri-operative odds of cognitive deficits until radiotherapy follows. Finally, a tract based spatial statistics study using diffusion tensor MRI brain scans demonstrates that a common anatomical mechanism exists, affecting the same right hemisphere white matter tracts underlying social cognition deficits in participants with glioblastoma as is seen in traumatic brain injury and neurodegenerative disease contexts. 3 By contributing new knowledge, research methodology, immediately translational implications for clinical practice and by linking the mechanisms of cognitive deficits between glioblastoma and other neurological diseases, the results herein have already secured further research funding. This future work will build on the understanding of cognitive deficits presented here and to trial a targeted rehabilitation intervention to help people with glioblastoma and their families.
Cognition, Cancer, Neurosurgery, Glioblastoma, Surgery, Oncology
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