Understanding the difference in symptoms and outcomes between glioblastoma patients diagnosed based on histological or molecular criteria: a retrospective cohort analysis from the Histo-Mol GBM collaborative

Understanding the difference in symptoms and outcomes between glioblastoma patients diagnosed based on histological or molecular criteria: a retrospective cohort analysis from the Histo-Mol GBM collaborative | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding the difference in symptoms and outcomes between glioblastoma patients diagnosed based on histological or molecular criteria: a retrospective cohort analysis from the Histo-Mol GBM collaborative Stephen David Robinson, Sarah Kingdon, Sophie Therese Williams, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7401683/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Journal of Neuro-Oncology → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose: Since the 2021 World Health Organisation (WHO) classification, glioblastoma could be diagnosed based on classical histological features (hGBM) or molecular criteria (mGBM). However, prior studies included patients who required reclassification as a mGBM, potentially biasing survival analyses. The Histo-Mol GBM collaborative performed an international multicentre retrospective real-world cohort study of glioblastoma patients diagnosed according to WHO CNS 5. Methods: We identified consecutive patients diagnosed in 2021 with IDH wildtype glioblastoma according to WHO CNS 5. Clinicopathological, treatment, and survival data were collected and compared between mGBM and hGBM. Results: 1828 patients diagnosed with glioblastoma were included. 75 mGBM patients (8.4% of tested patients) were identified, with no difference in age (median 61 vs 64, p=0.057), gender (p=0.937), or proportion with performance status 0-1 (82.7% vs 68.3%, p=0.052) compared to hGBM. mGBM patients had an extended interval from MRI to surgery (median 23 vs 14 days, p<0.001) and more frequently underwent biopsy (69.3% vs 30.3%, p<0.001), but equivalent proportions received oncological treatment (80.0% vs 78.7%, p=0.784). Overall survival (OS) from surgery was not different (p=0.063). However, OS from initial MRI, stratified by surgical extent, demonstrated improved OS for mGBM patients (hazard ratio (HR) 0.56, 95% confidence interval (CI): 0.43-0.73). Propensity score matching identified improved survival following resection (HR 0.48, 95% CI: 0.24-0.95; median OS: 26.0 versus 14.0 months, p=0.031) but not biopsy (HR 1.10, 95% CI: 0.71-1.72). Conclusion: In this large real-world cohort, mGBMs had longer OS than hGBMs following resection with implications for prognostication and clinical decision making. Glioblastoma Molecular Glioblastoma Survival Real-World Evidence Histology Classification Figures Figure 1 Figure 2 Figure 3 Introduction Advances in understanding the molecular drivers of gliomagenesis has led to significant changes in brain tumour classification. Following the “Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy” (cIMPACT-NOW)[ 1 ] and the 2021 World Health Organisation (WHO) Classification of Tumours of the Central Nervous System (CNS)[ 2 ], glioblastoma could be diagnosed by meeting histopathological criteria (necrosis and microvascular proliferation, hGBM) or identifying specific molecular features (mGBM). These classifications[ 2 , 3 ] define mGBM as an adult-type isocitrate dehydrogenase-wildtype (IDHwt) and histone H3 wildtype diffuse astrocytic glioma with molecular testing that identifies at least one of: a telomerase reverse transcriptase promoter (pTERT) mutation, epidermal growth factor receptor (EGFR) amplification, or the combined gain of chromosome 7 and loss of chromosome 10 (Chr 7+/10-), and without meeting histopathological criteria. This classification change followed the identification that patients with histologically low grade IDHwt tumours with these molecular features had worse survival than would be expected for IDHwt tumours without these molecular features[ 4 – 6 ]. However, prior studies included mGBM patients who were diagnosed over extended time periods, often spanning multiple diagnostic classification changes[ 7 – 12 ]. This required patient reclassification and often included historical control arms, which could have introduced bias into subsequent survival analyses comparing mGBM and hGBM patients[ 13 ]. To overcome previous limitations, we performed an international multicentre retrospective real-world cohort study, including consecutive IDHwt glioblastoma patients diagnosed in a single year according to WHO CNS 5, to compare presentation, tumour, and treatment characteristics plus survival outcomes between mGBM and hGBM patients. Materials and methods We followed Strengthening Reporting of Observational Studies in Epidemiology (STROBE)[ 14 ] guidelines for this retrospective cohort study. Study approval: This study was approved by the University Hospitals Sussex (UHSussex) Clinical Outcomes and Effectiveness Committee (ref:1862) who confirmed the exemption for gaining patient consent. Institutional review board approval, including information governance agreement, was required from each participating centre. New Zealand approval was provided from the Health and Disabilities Ethics Committee (ref:2024EXP21165) and the University of Otago Human Ethics Committee (Health) (ref:HD24/002). This study was conducted in accordance with the Declaration of Helsinki and all national and local regulations. Participants: We identified consecutive patients diagnosed with an IDHwt glioblastoma, according to WHO CNS 5, from 51 participating centres across three countries (Appendix 2), who underwent their diagnostic procedure between 01/01/2021-31/12/2021. Patients were identified and cross-referenced from local neuropathology, neurosurgery, and/or neuro-oncology records. Patients who had opted out of health record sharing through the United Kingdom National Data Opt-Out scheme (or equivalent) were excluded. Patients were diagnosed and treated according to local protocol. Data collection: We collected patient demographics, alongside presentation, tumour, and treatment characteristics, plus survival data (Appendix 3) locally from clinical records. Data was uploaded and managed using REDCap[ 15 ] electronic data capture tools, a secure online application designed for participant-based research, hosted at UHSussex. Molecular testing was performed according to local practice. O6-methylguanine methyltransferase (MGMT) promoter methylation status was categorised as unmethylated (0–10%) or methylated (> 10%)[ 16 ]. Given the challenges assessing extent of resection retrospectively, especially for non-contrast enhancing tumours, surgery was classified as biopsy or resection. Oncological treatment was categorised as: none, temozolomide alone, hypofractionated radiotherapy (40–53 Gray in > 2 Gray/fraction), hypofractionated chemoradiotherapy (hypofractionated radiotherapy plus concurrent temozolomide), conventionally fractionated chemoradiotherapy (54–60 Gray in 1.8-2 Gray/fraction plus concurrent temozolomide), or other treatment. Treatment was further categorised as: surgery only, intermediate (oncological treatment not meeting the criteria for aggressive), and aggressive (radiotherapy ≥ 40 Gray with concurrent temozolomide)[ 17 ]. Overall survival (OS) was calculated from date of surgery or date of MRI identifying a brain lesion subsequently confirmed to be glioblastoma (as specified) until death from any cause or censored at date of last follow up (neurosurgical/neurooncology clinic or brain MRI). Progression free survival (PFS) was calculated from date of surgery to MRI defined or neurosurgeon/neurooncologist defined clinical progression or censored at date of death/ last follow up. Statistical analysis: Statistical analysis was performed using SPSS statistical software (version 29.0.2.0, Chicago, IL). Differences in categorical variables were assessed by chi-squared test, whilst continuous variables were assessed by Mann-Whitney U test. Standardised mean difference was calculated using Cohen’s d or Glass’s delta as appropriate. Length of follow up was calculated using the reverse Kaplan-Meier technique. Survival analysis was performed using Kaplan-Meier methodology with log rank test for significance. The Cox proportional hazards regression model was used for univariate and multivariate analysis (if univariate p-value < 0.05). Differences were considered statistically significant when the two-sided p-value was < 0.05. To detect a survival difference of 26%[ 13 ] between mGBM and hGBM patients at 90% power and an expected frequency of 10% mGBM, a total of 410 patients would be required. Propensity score matching (PSM) was performed to minimise the impact of confounding factors on survival analysis. Initially, a binomial logistic regression was performed using the identified patient, tumour, and treatment feature differences. Subsequently, PSM was performed based on the features identified from the binomial logistic regression plus those identified in the multivariate analysis and using a match tolerance of 0.05. Results A total of 1828 patients were diagnosed with an IDHwt glioblastoma in 2021 from 51 centres (Appendix 2). Rates of molecular testing ranged from 0-100% across centres (median 38% of patients tested) (Supplementary Figure 1) and 895 patients (49% of patients) underwent molecular testing during their diagnostic pathway. Of these, 75 patients were diagnosed with a mGBM (8.4%), with a similar proportion of mGBM patients (15/173, 8.7%) identified from the six centres who performed molecular testing in all patients. Comparison of patient and tumour characteristics of mGBM and hGBM patients: The majority of mGBM patients were male with no difference compared to hGBM (64% vs 64%, p=0.937) and with a similar age at presentation (median 61 vs 64 years, p=0.057). Additionally, there was no difference in WHO performance status (PS) at presentation (p=0.152), with similar proportions of patients with PS 0-1 (83% vs 68%, p=0.052) (Table 1). However, symptoms present at diagnosis differed, with more mGBM patients reporting seizures (41% vs 26%, p=0.003), including an increase in pre-operative anti-epileptic drug (AED) prescriptions (60% vs 45%, p=0.007), and sensory symptoms (21% vs 11%, p=0.006), alongside more incidental diagnoses (5.3% vs 1.3%, p=0.006). Further, fewer mGBM patients reported motor (21% vs 38%, p=0.003), speech (15% vs 29%, p=0.007), cognitive (11% vs 27%, p=0.002), and headache (20% vs 34%, p=0.011) symptoms at diagnosis, and had fewer pre-operative corticosteroids prescribed (57% vs 79%, p<0.001) (Table 1). Tumour location differed with greater numbers of mGBM tumours involving the parietal lobe (44% vs 30%, p=0.012) and cerebellum (4.0% vs 1.3%, p=0.045). Additionally, there were more multifocal/multicentric (37% vs 24%, p=0.010) and non-contrast enhancing tumours (27% vs 3.7%, p<0.001) in mGBM patients. Most mGBM patients’ tumours displayed histological features equating to grade 3 (62/75, 83%) with a minority of grade 2 tumours (13/75, 17%) (Table 1). For the patients whose tumours underwent molecular testing, there was no difference in the proportion of tumours with methylated MGMT (17% vs 26%, p=0.096), EGFR amplification (42% vs 37%, p=0.416), or Chr 7+/10- (53% vs 37%, p=0.068). However, more mGBM patients had tumours with a pTERT mutation (89% vs 78%, p=0.035) (Table 1). Focussing on the mGBM cohort, Figure 1 demonstrates the composition of defining molecular alterations for the patients diagnosed with a mGBM. Of the 75 mGBM patients identified, 49 patients (65%) had a singular defining molecular feature identified, 21 (28%) had two features, and five (6.7%) had all three features (Figure 1a). However, most patients’ tumours underwent partial molecular testing, with only 29 patients’ tumours (39%) undergoing comprehensive molecular characterisation. In this subgroup, 14 patients (48%) had a singular molecular feature, predominantly pTERT mutation only (11 patients, 38%), 10 patients (35%) had two features, and five patients (17%) had all three features identified. Comparison of treatment characteristics of mGBM and hGBM patients: Patients with mGBM had an extended interval from MRI to surgery (23 vs 14 days, p<0.001). Additionally, the majority of mGBM patients had a biopsy compared to a much lower proportion of hGBM patients (69% vs 30%, p<0.001) (Table 1). There was also an extended time from surgery to radiotherapy (if received) for mGBM patients (46 vs 40 days, p=0.002) in keeping with a delay in receiving the final molecular histopathology report prior to definitive decision making. However, there was no difference in the oncological treatment received, with equal proportions of patients receiving any treatment (80% vs 79%, p=0.784), and equivalent proportions receiving conventionally fractionated chemoradiotherapy (41% vs 43%, p=0.784) (Table 1). Comparison of PFS and OS for mGBM and hGBM patients: Progressive disease (either clinical or radiological) was documented in around three quarters of mGBM and hGBM patients (76% vs 76%, p=0.921) (Table 2) with similar median PFS from surgery of 6.9 months (95% confidence interval (CI) 4.8-9.0 months) for mGBM compared to 7.2 months (95% CI 6.7-7.7 months, p=0.319) for hGBM patients (Figure 2A). Following progression, similar proportions of patients received subsequent treatment (49% vs 42%, p=0.300). At the time of analysis, equivalent proportions of patients remained alive (15% vs 13%, p=0.643) with equal median length of follow up (33.8 vs 34.2 months, p=0.584) (Table 1). Kaplan-Meier survival analysis demonstrated no clear difference between groups, with median OS from surgery of 13.8 months (95% CI: 10.3-17.4 months) for mGBM patients compared to 10.3 months (95% CI: 9.7-10.9 months, p=0.063) for hGBM patients (Figure 2B). However, as demonstrated in Table 1, there was an increase in the time from MRI to surgery and differences in the surgery performed, both of which are likely to impact OS. Repeating the Kaplan-Meier analysis when computing OS from MRI scan and stratifying by surgical approach demonstrated that mGBM patients have improved OS compared to hGBM patients (hazard ratio (HR) 0.56, 95% CI: 0.434-0.730) (Figure 2C,D). For patients who underwent neurosurgical biopsy (HR 0.61, 95% CI: 0.45-0.82), median OS from MRI for mGBM patients was 10.7 months (95% CI: 7.1-14.2 months) compared to 6.3 months (95% CI: 5.6 vs 7.0 months, p=0.001) for hGBM patients (Figure 2C). Whilst for patients who underwent resection (HR 0.45, 95% CI: 0.26-0.77), median OS from MRI was 26.0 months (95% CI: 20.7-31.2 months) for mGBM compared to 13.0 months (95% CI: 12.3-13.7 months, p=0.003) for hGBM patients (Figure 2D). Analysis of factors associated with OS in mGBM patients: Univariate Cox regression analysis identified that increasing age (p=0.007), presenting with motor (p=0.004), behavioural (p 2 (p=0.006) or a multifocal/multicentric tumour (p=0.048) were associated with worse OS for mGBM patients, whilst presenting with seizures (p<0.001), receiving an anti-epileptic drug (AED) at diagnosis (p=0.002), undergoing resection (p=0.001), or increasing intensity of oncological treatment (p<0.001) were associated with improved OS (Table 2). On multivariate analysis, presenting with motor symptoms (HR 2.71, 95% CI: 1.19-6.16, p=0.018) or reduced GCS (HR 13.40, 95% CI: 2.05-87.41, p=0.007), receiving an AED at diagnosis (HR 0.33, 95% CI: 0.41-0.80, p=0.013), and increasing intensity of oncological treatment (Aggressive > Intermediate > Surgery only; HR 0.46, 95% CI: 0.25-0.83, p=0.010) remained as prognostic factors for mGBM patients (Table 2). Comparison of survival in propensity score matched mGBM and hGBM patients: To identify the features most associated with an mGBM diagnosis, a binomial logistic regression (Supplementary Table 1) was performed using the differences identified between mGBM and hGBM (Table 1). Subsequently, these features, plus the features associated with mGBM patient OS on multivariate analysis (Table 2), were used to perform PSM. After applying PSM, the balance of covariates between groups improved and potential confounding was reduced (Figure 3A,B). The improved similarities of the patient, tumour and treatment variables for the 75 mGBM patients and the 67 matched hGBM patients (Table 1) confirm the effectiveness of the matching, although some differences remained. Comparing OS between these matched groups (Figure 3C,D) identified no difference in survival for patients who undergo biopsy (HR 1.10, 95% CI: 0.71-1.72) with a median OS of 10.7 months (95% CI: 7.1-14.2 months) for mGBM patients compared to 13.0 months (95% CI: 8.2-17.7 months, p=0.667) for hGBM patients (Figure 3C). However, in patients who undergo resection, mGBM patients have a better prognosis (HR 0.48, 95% CI: 0.24-0.95), with a median OS of 26.0 months (95% CI: 20.7-31.2 months) compared to 14.0 months (95% CI: 8.8-19.2 months, p=0.031) for hGBM patients (Figure 3D). Discussion The 2021 WHO CNS classification[ 2 ] marked a foundational shift in neuro-oncology, through including molecular features within a final integrated diagnosis. However, several studies have published discordant results when assessing whether mGBM patient survival is equivalent to hGBM patients[ 7 , 10 – 13 , 18 – 20 ]. One challenge of using retroactively reclassified patients, is that long study periods or comparisons with historical controls will potentially introduce bias related to changes in clinical practice over time[ 21 ]. To overcome this challenge, we developed a large, international, multicentre cohort database of 1828 patients consecutively diagnosed during a single year with a pathologically confirmed IDHwt glioblastoma according to WHO CNS 5. This unique dataset enables population level comparisons of equivalent mGBM and hGBM patients, diagnosed and treated according to the same local protocols, using granular individual patient data. Compared to previous studies[ 12 , 22 ], we identified no difference in age, or other demographics, between mGBM and hGBM patients. However, we identified differences in clinical presentation, with mGBM patients more commonly describing seizures and sensory changes, but less frequently describing motor, speech or cognitive symptoms, similar to the study by Guo et al .[ 10 ], which likely explains the differences identified in AED and steroid prescriptions at diagnosis. This altered symptom profile has implications for the diagnostic pathway as this pattern of symptoms is less common with hGBM[ 23 ] and, alongside the lower proportion of contrast enhancing lesions (72% vs 95%), increases the diagnostic uncertainty due to the overlap between these findings and encephalitis and/or cerebral vasculitis[ 24 , 25 ]. This may explain the extended interval between MRI and surgery (median 9 days delay) for mGBM patients and emphasises the need for robust diagnostic pathways to pathologically confirm radiologically “low-grade” patients. In keeping with other published studies, we identified that mGBM patients were more likely to have multifocal/multicentric tumours (37% vs 24%) and to undergo biopsy rather than resection (69% vs 30%)[ 11 – 13 ]. These overlapping features, alongside the presence of the gliomatosis cerebri pattern described previously[ 7 , 12 ], has raised the concern that a proportion of mGBM patients may have an “under-sampled” hGBM[ 19 ]. Currently, standard surgical practice is to sample an area of contrast enhancement (where present), supplemented by further imaging modalities depending on local practice, that is presumed representative of the highest grade of the tumour[ 26 ]. However, whilst our initial analysis identified improved outcomes for mGBM patients following biopsy (HR 0.61, 95% CI: 0.45–0.82), after PSM we demonstrated equivalent survival (HR 1.10, 95% CI: 0.71–1.72). This suggests that PSM removed unidentified confounders and highlights the difficulty in accurately identifying mGBM on biopsy samples. The main finding from this study is that patients with mGBM have a longer OS compared to hGBM patients following resection (HR 0.45, 95% CI: 0.26–0.77), which we confirmed through PSM (HR 0.48, 95% CI: 0.24–0.95). Given the longer OS (median OS 26.0 vs 13.0 months) for patients after resection, there is an argument for considering subsequent resection when technically feasible following the identification of an mGBM on biopsy, to confirm the diagnosis and representing a form of molecularly-based decision-making[ 27 ]. This OS improvement is in keeping with a previous meta-analysis from 2023[ 13 ], which demonstrated improved survival on multivariate analysis (HR 0.61, 95% CI: 0.50–0.74), although most of the included studies identified no clear difference in OS[ 7 , 9 , 10 , 18 , 22 , 28 , 29 ]. One explanation for this difference is that these studies may have been underpowered to detect a difference, and that the proportion of resection cases differed between studies. Additionally, several studies identified less intensive oncological treatment for mGBM patients[ 7 , 22 , 28 , 29 ]. Further, we identified that systematic differences in the diagnostic pathway impact OS outcomes, which may also explain some of the disparate findings in prior studies. Whilst the impact of an extended interval from MRI to surgery raises the possibility that this OS difference may be due to lead time bias, the difference in median interval from MRI to surgery is only 9 days, which is unlikely to be the defining difference. Given the OS difference identified, we suggest routinely collecting information on molecular vs histological diagnosis of glioblastoma for trial participants and considering stratifying for mGBM vs hGBM at trial entry, given the risk that potentially important survival improvements may be obscured by imbalances in patients between treatment arms. Limitations: A limitation of this study is that including patients diagnosed during 2021 meant that some centres were experiencing ongoing SARS-COV2 related pressures[ 30 , 31 ], including centres with reduced surgical capacity leading to a 50% reduction in the number of pathologically confirmed glioblastoma patients (personal communication). The exclusion of poor prognostic patients may have led to an improvement in OS. However, the reported PFS and OS for hGBM patients are in keeping with previously published results[ 17 ], suggesting that SARS-COV2 related adjustments had limited influence on survival in this cohort. Further, WHO CNS 5 was published in June 2021[ 2 ], although cIMPACT-NOW update 3 was published in 2018[ 3 ]. Therefore, most centres were not performing routine molecular testing for all (n = 36 centres) or any (n = 9 centres) glioblastoma patients, which may have led to an under-diagnosis of mGBM in this study. However, similar proportions of mGBM patients were identified at centres with complete molecular testing (8.7%) and the whole cohort (8.4%) providing confidence in this estimate. However, we would encourage comprehensive molecular testing as ~ 10–21% of mGBM patients would be missed by only assessing pTERT. Additionally, the small numbers of mGBM patients compared to hGBM limits the power of subgroup analyses, potentially obscuring true differences. Conclusion In conclusion, we present a comparison of mGBM and hGBM patients diagnosed according to WHO CNS 5 using a large real-world cohort. We demonstrate that glioblastoma patients diagnosed according to molecular features, are uncommon (< 10%), and differ compared to those diagnosed based on classical histological criteria. We also identify that mGBM patients had longer OS than hGBM patients following resection with implications for clinical decision making, prognostic estimates given to patients, and clinical trial enrolment. Declarations Conflicts of interest: The authors declare no conflicts of interest. Funding Dr Stephen David Robinson is funded by a University Hospitals Sussex NHS Foundation Trust Medical Doctoral Fellowship. Dr Sarah Kingdon is currently supported by the Tessa Jowell Brain Cancer Mission Fellowship Programme, funded by Beatson Cancer Charity, NHS Lothian Charity, and the Chief Scientist Office. Mr Ciaran Scott Hill is funded by the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre. These funders had no involvement in the design or conduct of the study. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution 1 guarantor of integrity of the entire study: S.D.R. and G.C.; 2 study concepts and design: S.D.R., E.C. and G.C.; 3 literature research: S.D.R.; 4 clinical studies: S.D.R, S.K., S.T.W, G.C. and Histo-Mol GBM Collaborative; 5 experimental studies / data analysis: NA; 6 statistical analysis: S.D.R.; 7 manuscript preparation: S.D.R.; 8 manuscript editing: S.K., S.T.W, C.S.H., M.W., E.C., G.C. and Histo-Mol GBM Collaborative. Acknowledgement We would like to thank Duncan Fatz and Vittorio Trevitt for their invaluable support with REDCap. We would also like to thank everyone who supported with patient identification and data management at each of the participating centres. 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Neurooncol Adv 3: vdab014 10.1093/noajnl/vdab014 Tables Characteristic Unmatched PSM matched mGBM n (%) hGBM n (%) p-value SMD mGBM n (%) hGBM n (%) p-value SMD Number of patients N=75 N=1753 N=75 N=67 Patient Factors Gender: Male Female 48 (64.0%) 27 (36.0%) 1114 (63.5%) 639 (36.5%) 0.937 0.009 48 (64.0%) 27 (36.0%) 44 (65.7%) 23 (34.3%) 0.835 0.035 Age (years): Median Range 61 24-87 64 18-88 0.057 0.230 61 24-87 62 24-83 0.954 0.047 WHO PS at diagnosis: 0 1 2 3 4 Unknown 32 (42.7%) 30 (40.0%) 6 (8.0%) 2 (2.7%) 0 (0.0%) 5 (6.7%) 498 (28.4%) 700 (39.9%) 244 (13.9%) 63 (3.6%) 12 (0.7%) 236 (13.5) 0.152 0.300 32 (42.7%) 30 (40.0%) 6 (8.0%) 2 (2.7%) 0 (0.0%) 5 (6.7%) 12 (18.0%) 36 (53.7%) 11 (16.4%) 5 (7.5%) 0 (0%) 3 (4.5%) 0.007 0.581 WHO PS at diagnosis: 0-1 2+ Unknown 62 (82.7%) 8 (10.7%) 5 (6.7%) 1198 (68.3%) 319 (18.2%) 236 (13.5%) 0.052 0.235 62 (82.7%) 8 (10.7%) 5 (6.7%) 48 (71.6%) 16 (23.9%) 3 (4.5%) 0.041 0.424 Presenting symptom - Seizure: Yes No 31 (41.3%) 44 (58.7%) 451 (25.7%) 1302 (74.3%) 0.003 0.357 31 (41.3%) 44 (58.7%) 39 (58.2%) 28 (41.8%) 0.045 0.340 Presenting symptom - Motor: Yes No 16 (21.3%) 59 (78.7%) 667 (38.0%) 1086 (62.0%) 0.003 0.344 16 (21.3%) 59 (78.7%) 13 (19.4%) 54 (80.6%) 0.776 0.048 Presenting symptom - Sensory: Yes No 16 (21.3%) 59 (78.7%) 194 (11.1%) 1559 (88.9%) 0.006 0.327 16 (21.3%) 59 (78.7%) 13 (19.4%) 54 (80.6%) 0.776 0.048 Presenting symptom - Speech: Yes No 11 (14.7%) 64 (85.3%) 510 (29.1%) 1243 (70.9%) 0.007 0.318 11 (14.7%) 64 (85.3%) 13 (19.4%) 54 (80.6%) 0.452 0.126 Presenting symptom - Cognition: Yes No 8 (10.7%) 67 (89.3%) 475 (27.1%) 1278 (72.9%) 0.002 0.370 8 (10.7%) 67 (89.3%) 17 (25.4%) 50 (74.6%) 0.022 0.473 Presenting symptom - Behaviour: Yes No 4 (5.3%) 71 (94.7%) 134 (7.6%) 1619 (92.4%) 0.458 0.087 4 (5.3%) 71 (94.7%) 4 (6.0%) 63 (94.0%) 0.869 0.027 Presenting symptom - Visual: Yes No 5 (6.7%) 70 (93.3%) 168 (9.6%) 1585 (90.4%) 0.398 0.100 5 (6.7%) 70 (93.3%) 8 (11.9%) 59 (88.1%) 0.277 0.210 Presenting symptom - Headache: Yes No 15 (20.0%) 60 (80.0%) 600 (34.2%) 1153 (65.8%) 0.011 0.300 15 (20.0%) 60 (80.0%) 25 (37.3%) 42 (62.7%) 0.022 0.430 Presenting symptom – Reduced GCS: Yes No 2 (2.7%) 73 (97.3%) 75 (4.3%) 1678 (95.7%) 0.496 0.080 2 (2.7%) 73 (97.3%) 1 (1.5%) 66 (98.5%) 0.627 0.081 Presenting symptom - Incidental: Yes No 4 (5.3%) 71 (94.7%) 23 (1.3%) 1730 (98.7%) 0.005 0.178 4 (5.3%) 71 (94.7%) 0 (0%) 67 (100%) 0.055 0.236 Presenting symptom – Other: Yes No 15 (20.0%) 60 (80.0%) 236 (13.5%) 1517 (86.5%) 0.107 0.190 15 (20.0%) 60 (80.0%) 12 (17.9%) 55 (82.1%) 0.751 0.053 Corticosteroids at diagnosis: Yes No Unknown 43 (57.3%) 30 (40.0%) 2 (2.7%) 1392 (79.4%) 322 (18.4%) 39 (2.2%) <0.001 0.571 43 (57.3%) 30 (40.0%) 2 (2.7%) 56 (83.6%) 11 (17.9%) 0 (0%) 0.001 0.498 Anti-epileptic drugs at diagnosis: Yes No Unknown 45 (60.0%) 29 (38.7%) 1 (1.3%) 780 (44.5%) 960 (54.8%) 13 (0.7%) 0.007 0.321 45 (60.0%) 29 (38.7%) 1 (1.3%) 55 (82.1%) 12 (17.9%) 0 (0%) 0.005 0.433 Tumour Factors Tumour Location: Left Right Midline/bilateral 39 (52.0%) 31 (41.3%) 5 (6.7%) 788 (45.0%) 868 (49.5%) 95 (5.4%) 0.373 0.097 39 (52.0%) 31 (41.3%) 5 (6.7%) 35 (52.2%) 29 (43.3%) 3 (4.5%) 0.847 0.040 Tumour Location*: Frontal Parietal Temporal Occipital Cerebellum Brainstem 25 (33.3%) 33 (44.0%) 37 (49.3%) 5 (6.7%) 3 (4.0%) 4 (5.3%) 653 (37.3%) 530 (30.3%) 754 (43.0%) 157 (9.0%) 22 (1.3%) 42 (2.4%) 0.492 0.012 0.279 0.494 0.045 0.112 0.081 0.298 0.128 0.081 0.247 0.192 25 (33.3%) 33 (44.0%) 37 (49.3%) 5 (6.7%) 3 (4.0%) 4 (5.3%) 22 (32.8%) 27 (40.3%) 30 (44.8%) 10 (14.9%) 0 (0%) 3 (4.5%) 0.950 0.656 0.587 0.110 0.098 0.814 0.010 0.074 0.091 0.329 0.203 0.039 Multifocal/multicentric tumour: Yes No Unknown 28 (37.3%) 47 (62.7%) 0 (0.0%) 423 (24.1%) 1328 (75.8%) 2 (0.1%) 0.010 0.308 28 (37.3%) 47 (62.7%) 0 (0.0%) 19 (28.4%) 48 (71.6%) 0 (0%) 0.257 0.184 Contrast enhancing on MRI: Yes No Unknown 54 (72.0%) 20 (26.7%) 1 (1.3%) 1667 (95.1%) 64 (3.7%) 22 (1.3%) <0.001 1.236 54 (72.0%) 20 (26.7%) 1 (1.3%) 66 (98.5%) 1 (1.5%) 0 (0%) <0.001 0.571 Grade: 2 3 4 Unknown/Ungraded 13 62 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1688 (96.3%) 65 (3.7%) <0.001 5.659 13 62 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 67 (100%) 0 (0%) <0.001 2.992 Molecular markers – pTERT # : Yes No Not tested 59 (89.4%) 7 (10.6%) 9 507 (78.4%) 140 (21.6%) 1075 0.035 1.107 59 (89.4%) 7 (10.6%) 9 52 (91.2%) 5 (8.8%) 10 0.828 0.056 Molecular markers – EGFR # : Yes No Not tested 28 (42.4%) 38 (67.9%) 9 240 (37.3%) 403 (62.7%) 1060 0.416 1.031 28 (42.4%) 38 (67.9%) 9 25 (41.0%) 36 (59.0%) 4 0.922 0.021 Molecular markers – Chr 7+/10- # : Yes No Not tested 19 (52.8%) 17 (47.2%) 39 87 (36.9%) 149 (63.1%) 1453 0.068 1.107 19 (52.8%) 17 (47.2%) 39 7 (70.0%) 3 (30.0%) 56 10%) Unknown 62 (82.7%) 13 (17.3%) 0 (0.0%) 1241 (70.8%) 454 (25.9%) 58 (3.3%) 0.096 0.225 62 (82.7%) 13 (17.3%) 0 (0.0%) 60 (89.6%) 7 (10.4%) 0 (0%) 0.239 0.181 Treatment Factors Time from MRI to surgery: Median Range 23 0-869 14 0-1395 <0.001 0.686 23 0-869 17 0-1395 0.009 0.001 Extent of surgery: Biopsy Resection Unknown 52 (69.3%) 23 (30.7%) 0 (0.0%) 532 (30.3%) 1214 (69.3%) 7 (0.4%) <0.001 0.847 52 (69.3%) 23 (30.7%) 0 (0.0%) 39 (58.2%) 28 (41.8%) 0 (0%) 0.168 0.240 Time from surgery to radiotherapy: Median Range 46 12-108 40 9-245 0.002 0.381 46 12-108 39 22-115 0.004 0.406 Oncological treatment: None Temozolomide Hypofractionated RT Hypofractionated CRT Conventional CRT Other treatments 15 (20.0%) 4 (5.3%) 8 (10.7%) 10 (13.3%) 31 (41.3%) 7 (9.3%) 374 (21.3%) 49 (2.8%) 196 (11.2%) 225 (12.8%) 752 (42.9%) 157 (9.0%) 0.784 0.015 15 (20.0%) 4 (5.3%) 8 (10.7%) 10 (13.3%) 31 (41.3%) 7 (9.3%) 14 (20.9%) 6 (9.0%) 8 (11.9%) 7 (10.4%) 31 (46.3%) 1 (3.3%) 0.920 0.017 Oncological treatment: Surgery only Intermediate Aggressive 15 (20.0%) 19 (25.3%) 41 (54.7%) 374 (21.3%) 402 (22.9%) 977 (55.7%) 0.880 0.003 15 (20.0%) 19 (25.3%) 41 (54.7%) 14 (20.9%) 15 (22.4%) 38 (56.7%) 0.919 0.014 Progression factors Confirmed progression: Yes No 57 (76.0%) 18 (24.0%) 1294 (75.5%) 420 (24.5%) 0.921 0.012 57 (76.0%) 18 (24.0%) 50 (76.9%) 15 (23.1%) 0.898 0.022 Received 2 nd line treatment: Yes No 28 (49.1%) 29 (50.9%) 546 (42.2%) 748 (57.8%) 0.300 0.140 28 (49.1%) 29 (50.9%) 27 (54.0%) 23 (46.0%) 0.615 0.097 Survival/Follow up Patient surviving: Yes No 11 (14.7%) 64 (85.3%) 225 (12.8%) 1528 (87.2%) 0.643 0.055 11 (14.7%) 64 (85.3%) 10 (14.9%) 57 (85.1%) 0.965 0.007 Length of follow up: Median 95% confidence interval 33.8 months 29.7 – 37.8 34.2 months 33.1 – 35.2 0.584 33.8 months 29.7 – 37.8 30.9 months 23.5 – 38.2 0.262 Table 1. Comparison of patient, tumour, treatment, progression and follow up characteristics between molecular glioblastoma patients and histological glioblastoma patients with the significant features highlighted in bold . *combined percentages may exceed 100 from tumours occupying multiple lobes. # percentages and statistics calculated for tested patients only. PSM: propensity score matched; mGBM: molecular glioblastoma; hGBM, histological glioblastoma; SMD: standardised mean difference; WHO PS: World Health Organisation performance status; GCS: Glasgow Coma Score; MRI: magnetic resonance imaging; pTERT: telomerase reverse transcriptase promoter mutation; EGFR: epidermal growth factor receptor amplification; Chr 7+/10-: combined gain of chromosome 7 and loss of chromosome 10; MGMT: O6-methylguanine methyltransferase; RT: radiotherapy alone; CRT: concurrent chemoradiotherapy; Other treatments: other oncological treatments (conventionally fractionated radiotherapy alone, palliative radiotherapy, etc Variable Univariate Multivariate p value Hazard ratio (95% CI) p value Hazard ratio (95% CI) Age: Continuous 0.007 1.03 (1.01 – 1.06) 0.462 Gender: Male vs Female 0.968 Presenting symptom – Seizures: No vs Yes <0.001 0.36 (0.20 – 0.63) 0.474 Presenting symptom – Motor: No vs Yes 0.004 2.39 (1.32 – 4.31) 0.018 2.71 (1.19 – 6.16) Presenting symptom – Speech: No vs Yes 0.734 Presenting symptom – Cognition: No vs Yes 0.152 Presenting symptom – Behaviour: No vs Yes <0.001 14.02 (4.02 – 48.84) 0.101 Presenting symptom – Vision: No vs Yes 0.046 2.61 (1.02 – 6.68) 0.405 Presenting symptom – Headache: No vs Yes 0.052 Presenting symptom – Sensory: No vs Yes 0.742 Presenting symptom – Reduced GCS: No vs Yes 0.021 5.57 (1.29 – 23.99) 0.007 13.40 (2.05 – 87.41) Presenting symptom – Incidental: No vs Yes 0.860 Presenting symptom – Other: No vs Yes 0.451 Corticosteroids at diagnosis: No vs Yes 0.334 AEDs at diagnosis: No vs Yes 0.002 0.44 (0.26 – 0.74) 0.013 0.33 (0.41 – 0.80) WHO Performance status: 0-1 vs 2+ 0.006 3.27 (1.46 – 7.56) 0.059 Site: Left vs Right vs Midline/Bilateral 0.139 Frontal lobe: No vs Yes 0.545 Parietal lobe: No vs Yes 0.806 Temporal lobe: No vs Yes 0.431 Occipital lobe: No vs Yes 0.283 Cerebellum: No vs Yes 0.094 Brainstem: No vs Yes 0.368 Multifocal/multicentric: No vs Yes 0.048 1.69 (1.01 – 2.83) 0.271 Contrast enhancing on MRI: No vs Yes 0.125 Grade: 2 vs 3 0.161 MGMT methylation: No vs Yes 0.473 Surgery: Biopsy vs Resection 0.001 0.36 (0.19 – 0.67) 0.266 Oncological treatment: None vs Intermediate vs Aggressive <0.001 0.33 (0.22 – 0.48) 0.010 0.46 (0.25 – 0.83) Table 2. Univariate and multivariate Cox regression analysis for overall survival in molecular glioblastoma patients. Variables with p-value <0.05 on univariate analysis were chosen for assessment in the multivariate analysis with the significant features highlighted in bold . 95% CI: 95% confidence interval; GCS: Glasgow Coma Score; AEDs: Anti-epileptic drugs; WHO: World Health Organisation; MRI: Magnetic Resonance Imaging; MGMT: O6-methylguanine methyltransferase. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":74624,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams highlighting the overlap in the identification of the defining molecular alterations for the molecular glioblastoma patients within A) all patients and B) the subgroup of patients with comprehensive molecular testing. pTERT: telomerase reverse transcriptase promoter mutation; EGFR: epidermal growth factor receptor amplification; Chr 7+/10-: combined gain of chromosome 7 and loss of chromosome 10\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/07afdf8531aa01f084f3d880.jpg"},{"id":95314005,"identity":"7b1ae868-4224-4239-8697-ec850bc2a525","added_by":"auto","created_at":"2025-11-06 15:52:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":368783,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curves comparing survival between molecular glioblastoma patients and histological glioblastoma patients. A) Progression free survival and B) overall survival from date of surgery. Overall survival from date of initial magnetic resonance imaging for C) patients who underwent biopsy and D) patients who underwent resection. PFS: Progression free survival from date of surgery; hGBM: histological glioblastoma; mGBM: molecular glioblastoma; 95% CI: 95% confidence interval; OS: Overall survival; MRI: magnetic resonance imaging.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/5b51d9052671972690435676.jpg"},{"id":95283300,"identity":"b51af1c0-7db9-4b5e-999e-249e7ff18e58","added_by":"auto","created_at":"2025-11-06 09:36:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":295449,"visible":true,"origin":"","legend":"\u003cp\u003ePropensity score matching confirms the overall survival differences between molecular glioblastoma patients and histological glioblastoma patients. Scatter plot comparing the distribution of predicted probabilities of being a molecular glioblastoma generated from the binomial logistic regression analysis for A) the whole cohort and B) the propensity score matched cohort. Kaplan-Meier survival curves comparing the overall survival from date of initial magnetic resonance imaging between molecular glioblastoma patients and histological glioblastoma patients for C) patients who underwent biopsy and D) patients who underwent resection. 1 = molecular glioblastoma; 0 = histological glioblastoma; OS: Overall survival from date of surgery; hGBM: histological glioblastoma; mGBM: molecular glioblastoma; 95% CI: 95% confidence interval; MRI: magnetic resonance imaging.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/5322f254f81e814a15afda3d.jpg"},{"id":100069817,"identity":"98de9736-5e8f-4f66-8246-71ae26696c78","added_by":"auto","created_at":"2026-01-12 16:15:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2289652,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/810877c2-053f-459a-ba09-130a3c90f221.pdf"},{"id":95313501,"identity":"2c843722-861e-4dec-9c6a-0d46866efa42","added_by":"auto","created_at":"2025-11-06 15:51:33","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1576694,"visible":true,"origin":"","legend":"","description":"","filename":"RobinsonetalAppendix3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/c20339abeab8f1d881f6a1f0.docx"},{"id":95283295,"identity":"5a75232e-8a03-4fd9-9a0a-cc7d72ea917a","added_by":"auto","created_at":"2025-11-06 09:36:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23944,"visible":true,"origin":"","legend":"","description":"","filename":"RobinsonetalAppendix2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/47e484233499bf53a75f1533.docx"},{"id":95283294,"identity":"8b686ff3-2087-4742-8d5f-0542daae2b03","added_by":"auto","created_at":"2025-11-06 09:36:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":26269,"visible":true,"origin":"","legend":"","description":"","filename":"RobinsonetalAppendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/e712220ee4a83fbb67995d1c.docx"},{"id":95313962,"identity":"8032d479-b818-48ad-adb7-a921c5bbd194","added_by":"auto","created_at":"2025-11-06 15:52:17","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1733060,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-7401683/v1/60e0485956f73fd7a0d3d9be.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding the difference in symptoms and outcomes between glioblastoma patients diagnosed based on histological or molecular criteria: a retrospective cohort analysis from the Histo-Mol GBM collaborative","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAdvances in understanding the molecular drivers of gliomagenesis has led to significant changes in brain tumour classification. Following the \u0026ldquo;Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy\u0026rdquo; (cIMPACT-NOW)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and the 2021 World Health Organisation (WHO) Classification of Tumours of the Central Nervous System (CNS)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], glioblastoma could be diagnosed by meeting histopathological criteria (necrosis and microvascular proliferation, hGBM) or identifying specific molecular features (mGBM).\u003c/p\u003e\u003cp\u003eThese classifications[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] define mGBM as an adult-type isocitrate dehydrogenase-wildtype (IDHwt) and histone H3 wildtype diffuse astrocytic glioma with molecular testing that identifies at least one of: a telomerase reverse transcriptase promoter (pTERT) mutation, epidermal growth factor receptor (EGFR) amplification, or the combined gain of chromosome 7 and loss of chromosome 10 (Chr 7+/10-), and without meeting histopathological criteria. This classification change followed the identification that patients with histologically low grade IDHwt tumours with these molecular features had worse survival than would be expected for IDHwt tumours without these molecular features[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, prior studies included mGBM patients who were diagnosed over extended time periods, often spanning multiple diagnostic classification changes[\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This required patient reclassification and often included historical control arms, which could have introduced bias into subsequent survival analyses comparing mGBM and hGBM patients[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo overcome previous limitations, we performed an international multicentre retrospective real-world cohort study, including consecutive IDHwt glioblastoma patients diagnosed in a single year according to WHO CNS 5, to compare presentation, tumour, and treatment characteristics plus survival outcomes between mGBM and hGBM patients.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eWe followed Strengthening Reporting of Observational Studies in Epidemiology (STROBE)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] guidelines for this retrospective cohort study.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy approval:\u003c/h2\u003e\u003cp\u003eThis study was approved by the University Hospitals Sussex (UHSussex) Clinical Outcomes and Effectiveness Committee (ref:1862) who confirmed the exemption for gaining patient consent. Institutional review board approval, including information governance agreement, was required from each participating centre. New Zealand approval was provided from the Health and Disabilities Ethics Committee (ref:2024EXP21165) and the University of Otago Human Ethics Committee (Health) (ref:HD24/002). This study was conducted in accordance with the Declaration of Helsinki and all national and local regulations.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants:\u003c/h3\u003e\n\u003cp\u003eWe identified consecutive patients diagnosed with an IDHwt glioblastoma, according to WHO CNS 5, from 51 participating centres across three countries (Appendix 2), who underwent their diagnostic procedure between 01/01/2021-31/12/2021. Patients were identified and cross-referenced from local neuropathology, neurosurgery, and/or neuro-oncology records. Patients who had opted out of health record sharing through the United Kingdom National Data Opt-Out scheme (or equivalent) were excluded. Patients were diagnosed and treated according to local protocol.\u003c/p\u003e\n\u003ch3\u003eData collection:\u003c/h3\u003e\n\u003cp\u003eWe collected patient demographics, alongside presentation, tumour, and treatment characteristics, plus survival data (Appendix 3) locally from clinical records. Data was uploaded and managed using REDCap[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] electronic data capture tools, a secure online application designed for participant-based research, hosted at UHSussex.\u003c/p\u003e\u003cp\u003eMolecular testing was performed according to local practice. O6-methylguanine methyltransferase (MGMT) promoter methylation status was categorised as unmethylated (0\u0026ndash;10%) or methylated (\u0026gt;\u0026thinsp;10%)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Given the challenges assessing extent of resection retrospectively, especially for non-contrast enhancing tumours, surgery was classified as biopsy or resection. Oncological treatment was categorised as: none, temozolomide alone, hypofractionated radiotherapy (40\u0026ndash;53 Gray in \u0026gt;\u0026thinsp;2 Gray/fraction), hypofractionated chemoradiotherapy (hypofractionated radiotherapy plus concurrent temozolomide), conventionally fractionated chemoradiotherapy (54\u0026ndash;60 Gray in 1.8-2 Gray/fraction plus concurrent temozolomide), or other treatment. Treatment was further categorised as: surgery only, intermediate (oncological treatment not meeting the criteria for aggressive), and aggressive (radiotherapy\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;40 Gray with concurrent temozolomide)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOverall survival (OS) was calculated from date of surgery or date of MRI identifying a brain lesion subsequently confirmed to be glioblastoma (as specified) until death from any cause or censored at date of last follow up (neurosurgical/neurooncology clinic or brain MRI). Progression free survival (PFS) was calculated from date of surgery to MRI defined or neurosurgeon/neurooncologist defined clinical progression or censored at date of death/ last follow up.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis:\u003c/h2\u003e\u003cp\u003eStatistical analysis was performed using SPSS statistical software (version 29.0.2.0, Chicago, IL). Differences in categorical variables were assessed by chi-squared test, whilst continuous variables were assessed by Mann-Whitney U test. Standardised mean difference was calculated using Cohen\u0026rsquo;s d or Glass\u0026rsquo;s delta as appropriate. Length of follow up was calculated using the reverse Kaplan-Meier technique. Survival analysis was performed using Kaplan-Meier methodology with log rank test for significance. The Cox proportional hazards regression model was used for univariate and multivariate analysis (if univariate p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Differences were considered statistically significant when the two-sided p-value was \u0026lt;\u0026thinsp;0.05. To detect a survival difference of 26%[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] between mGBM and hGBM patients at 90% power and an expected frequency of 10% mGBM, a total of 410 patients would be required.\u003c/p\u003e\u003cp\u003ePropensity score matching (PSM) was performed to minimise the impact of confounding factors on survival analysis. Initially, a binomial logistic regression was performed using the identified patient, tumour, and treatment feature differences. Subsequently, PSM was performed based on the features identified from the binomial logistic regression plus those identified in the multivariate analysis and using a match tolerance of 0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 1828 patients were diagnosed with an IDHwt glioblastoma in 2021 from 51 centres (Appendix 2). Rates of molecular testing ranged from 0-100% across centres (median 38% of patients tested) (Supplementary Figure 1) and 895 patients (49% of patients) underwent molecular testing during their diagnostic pathway. Of these, 75 patients were diagnosed with a mGBM (8.4%), with a similar proportion of mGBM patients (15/173, 8.7%) identified from the six centres who performed molecular testing in all patients.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison of patient and tumour characteristics of mGBM and hGBM patients:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe majority of mGBM patients were male with no difference compared to hGBM (64% vs 64%, p=0.937) and with a similar age at presentation (median 61 vs 64 years, p=0.057). \u0026nbsp; Additionally, there was no difference in WHO performance status (PS) at presentation (p=0.152), with similar proportions of patients with PS 0-1 (83% vs 68%, p=0.052) (Table 1).\u003c/p\u003e\n\u003cp\u003eHowever, symptoms present at diagnosis differed, with more mGBM patients reporting seizures (41% vs 26%, p=0.003), including an increase in pre-operative anti-epileptic drug (AED) prescriptions (60% vs 45%, p=0.007), and sensory symptoms (21% vs 11%, p=0.006), alongside more incidental diagnoses (5.3% vs 1.3%, p=0.006). Further, fewer mGBM patients reported motor (21% vs 38%, p=0.003), speech (15% vs 29%, p=0.007), cognitive (11% vs 27%, p=0.002), and headache (20% vs 34%, p=0.011) symptoms at diagnosis, and had fewer pre-operative corticosteroids prescribed (57% vs 79%, p\u0026lt;0.001) (Table 1).\u003c/p\u003e\n\u003cp\u003eTumour location differed with greater numbers of mGBM tumours involving the parietal lobe (44% vs 30%, p=0.012) and cerebellum (4.0% vs 1.3%, p=0.045). Additionally, there were more multifocal/multicentric (37% vs 24%, p=0.010) and non-contrast enhancing tumours (27% vs 3.7%, p\u0026lt;0.001) in mGBM patients. Most mGBM patients’ tumours displayed histological features equating to grade 3 (62/75, 83%) with a minority of grade 2 tumours (13/75, 17%) (Table 1).\u003c/p\u003e\n\u003cp\u003eFor the patients whose tumours underwent molecular testing, there was no difference in the proportion of tumours with methylated MGMT (17% vs 26%, p=0.096), EGFR amplification (42% vs 37%, p=0.416), or Chr 7+/10- (53% vs 37%, p=0.068). However, more mGBM patients had tumours with a pTERT mutation (89% vs 78%, p=0.035) (Table 1).\u003c/p\u003e\n\u003cp\u003eFocussing on the mGBM cohort, Figure 1 demonstrates the composition of defining molecular alterations for the patients diagnosed with a mGBM. Of the 75 mGBM patients identified, 49 patients (65%) had a singular defining molecular feature identified, 21 (28%) had two features, and five (6.7%) had all three features (Figure 1a). However, most patients’ tumours underwent partial molecular testing, with only 29 patients’ tumours (39%) undergoing comprehensive molecular characterisation. In this subgroup, 14 patients (48%) had a singular molecular feature, predominantly pTERT mutation only (11 patients, 38%), 10 patients (35%) had two features, and five patients (17%) had all three features identified.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison of treatment characteristics of mGBM and hGBM patients:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePatients with mGBM had an extended interval from MRI to surgery (23 vs 14 days, p\u0026lt;0.001). Additionally, the majority of mGBM patients had a biopsy compared to a much lower proportion of hGBM patients (69% vs 30%, p\u0026lt;0.001) (Table 1). There was also an extended time from surgery to radiotherapy (if received) for mGBM patients (46 vs 40 days, p=0.002) in keeping with a delay in receiving the final molecular histopathology report prior to definitive decision making. However, there was no difference in the oncological treatment received, with equal proportions of patients receiving any treatment (80% vs 79%, p=0.784), and equivalent proportions receiving conventionally fractionated chemoradiotherapy (41% vs 43%, p=0.784) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison of PFS and OS for mGBM and hGBM patients:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eProgressive disease (either clinical or radiological) was documented in around three quarters of mGBM and hGBM patients (76% vs 76%, p=0.921) (Table 2) with similar median PFS from surgery of 6.9 months (95% confidence interval (CI) 4.8-9.0 months) for mGBM compared to 7.2 months (95% CI 6.7-7.7 months, p=0.319) for hGBM patients (Figure 2A). Following progression, similar proportions of patients received subsequent treatment (49% vs 42%, p=0.300).\u003c/p\u003e\n\u003cp\u003eAt the time of analysis, equivalent proportions of patients remained alive (15% vs 13%, p=0.643) with equal median length of follow up (33.8 vs 34.2 months, p=0.584) (Table 1). Kaplan-Meier survival analysis demonstrated no clear difference between groups, with median OS from surgery of 13.8 months (95% CI: 10.3-17.4 months) for mGBM patients compared to 10.3 months (95% CI: 9.7-10.9 months, p=0.063) for hGBM patients (Figure 2B).\u003c/p\u003e\n\u003cp\u003eHowever, as demonstrated in Table 1, there was an increase in the time from MRI to surgery and differences in the surgery performed, both of which are likely to impact OS. Repeating the Kaplan-Meier analysis when computing OS from MRI scan and stratifying by surgical approach demonstrated that mGBM patients have improved OS compared to hGBM patients (hazard ratio (HR) 0.56, 95% CI: 0.434-0.730) (Figure 2C,D). For patients who underwent neurosurgical biopsy (HR 0.61, 95% CI: 0.45-0.82), median OS from MRI for mGBM patients was 10.7 months (95% CI: 7.1-14.2 months) compared to 6.3 months (95% CI: 5.6 vs 7.0 months, p=0.001) for hGBM patients (Figure 2C). Whilst for patients who underwent resection (HR 0.45, 95% CI: 0.26-0.77), median OS from MRI was 26.0 months (95% CI: 20.7-31.2 months) for mGBM compared to 13.0 months (95% CI: 12.3-13.7 months, p=0.003) for hGBM patients (Figure 2D).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis of factors associated with OS in mGBM patients:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUnivariate Cox regression analysis identified that increasing age (p=0.007), presenting with motor (p=0.004), behavioural (p\u0026lt;0.001), or visual symptoms (0.046), reduced Glasgow Coma Score (GCS) (p=0.021), PS \u003cu\u003e\u0026gt;\u003c/u\u003e2 (p=0.006) or a multifocal/multicentric tumour (p=0.048) were associated with worse OS for mGBM patients, whilst presenting with seizures (p\u0026lt;0.001), receiving an anti-epileptic drug (AED) at diagnosis (p=0.002), undergoing resection (p=0.001), or increasing intensity of oncological treatment (p\u0026lt;0.001) were associated with improved OS (Table 2).\u003c/p\u003e\n\u003cp\u003eOn multivariate analysis, presenting with motor symptoms (HR 2.71, 95% CI: 1.19-6.16, p=0.018) or reduced GCS (HR 13.40, 95% CI: 2.05-87.41, p=0.007), receiving an AED at diagnosis (HR 0.33, 95% CI: 0.41-0.80, p=0.013), and increasing intensity of oncological treatment (Aggressive \u0026gt; Intermediate \u0026gt; Surgery only; HR 0.46, 95% CI: 0.25-0.83, p=0.010) remained as prognostic factors for mGBM patients (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison of survival in propensity score matched mGBM and hGBM patients:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo identify the features most associated with an mGBM diagnosis, a binomial logistic regression (Supplementary Table 1) was performed using the differences identified between mGBM and hGBM (Table 1). Subsequently, these features, plus the features associated with mGBM patient OS on multivariate analysis (Table 2), were used to perform PSM.\u003c/p\u003e\n\u003cp\u003eAfter applying PSM, the balance of covariates between groups improved and potential confounding was reduced (Figure 3A,B). The improved similarities of the patient, tumour and treatment variables for the 75 mGBM patients and the 67 matched hGBM patients (Table 1) confirm the effectiveness of the matching, although some differences remained.\u003c/p\u003e\n\u003cp\u003eComparing OS between these matched groups (Figure 3C,D) identified no difference in survival for patients who undergo biopsy (HR 1.10, 95% CI: 0.71-1.72) with a median OS of 10.7 months (95% CI: 7.1-14.2 months) for mGBM patients compared to 13.0 months (95% CI: 8.2-17.7 months, p=0.667) for hGBM patients (Figure 3C). However, in patients who undergo resection, mGBM patients have a better prognosis (HR 0.48, 95% CI: 0.24-0.95), with a median OS of 26.0 months (95% CI: 20.7-31.2 months) compared to 14.0 months (95% CI: 8.8-19.2 months, p=0.031) for hGBM patients (Figure 3D).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe 2021 WHO CNS classification[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] marked a foundational shift in neuro-oncology, through including molecular features within a final integrated diagnosis. However, several studies have published discordant results when assessing whether mGBM patient survival is equivalent to hGBM patients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. One challenge of using retroactively reclassified patients, is that long study periods or comparisons with historical controls will potentially introduce bias related to changes in clinical practice over time[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo overcome this challenge, we developed a large, international, multicentre cohort database of 1828 patients consecutively diagnosed during a single year with a pathologically confirmed IDHwt glioblastoma according to WHO CNS 5. This unique dataset enables population level comparisons of equivalent mGBM and hGBM patients, diagnosed and treated according to the same local protocols, using granular individual patient data.\u003c/p\u003e\u003cp\u003eCompared to previous studies[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], we identified no difference in age, or other demographics, between mGBM and hGBM patients. However, we identified differences in clinical presentation, with mGBM patients more commonly describing seizures and sensory changes, but less frequently describing motor, speech or cognitive symptoms, similar to the study by Guo \u003cem\u003eet al\u003c/em\u003e.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], which likely explains the differences identified in AED and steroid prescriptions at diagnosis. This altered symptom profile has implications for the diagnostic pathway as this pattern of symptoms is less common with hGBM[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and, alongside the lower proportion of contrast enhancing lesions (72% vs 95%), increases the diagnostic uncertainty due to the overlap between these findings and encephalitis and/or cerebral vasculitis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This may explain the extended interval between MRI and surgery (median 9 days delay) for mGBM patients and emphasises the need for robust diagnostic pathways to pathologically confirm radiologically \u0026ldquo;low-grade\u0026rdquo; patients.\u003c/p\u003e\u003cp\u003eIn keeping with other published studies, we identified that mGBM patients were more likely to have multifocal/multicentric tumours (37% vs 24%) and to undergo biopsy rather than resection (69% vs 30%)[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These overlapping features, alongside the presence of the gliomatosis cerebri pattern described previously[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], has raised the concern that a proportion of mGBM patients may have an \u0026ldquo;under-sampled\u0026rdquo; hGBM[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Currently, standard surgical practice is to sample an area of contrast enhancement (where present), supplemented by further imaging modalities depending on local practice, that is presumed representative of the highest grade of the tumour[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, whilst our initial analysis identified improved outcomes for mGBM patients following biopsy (HR 0.61, 95% CI: 0.45\u0026ndash;0.82), after PSM we demonstrated equivalent survival (HR 1.10, 95% CI: 0.71\u0026ndash;1.72). This suggests that PSM removed unidentified confounders and highlights the difficulty in accurately identifying mGBM on biopsy samples.\u003c/p\u003e\u003cp\u003eThe main finding from this study is that patients with mGBM have a longer OS compared to hGBM patients following resection (HR 0.45, 95% CI: 0.26\u0026ndash;0.77), which we confirmed through PSM (HR 0.48, 95% CI: 0.24\u0026ndash;0.95). Given the longer OS (median OS 26.0 vs 13.0 months) for patients after resection, there is an argument for considering subsequent resection when technically feasible following the identification of an mGBM on biopsy, to confirm the diagnosis and representing a form of molecularly-based decision-making[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis OS improvement is in keeping with a previous meta-analysis from 2023[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], which demonstrated improved survival on multivariate analysis (HR 0.61, 95% CI: 0.50\u0026ndash;0.74), although most of the included studies identified no clear difference in OS[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. One explanation for this difference is that these studies may have been underpowered to detect a difference, and that the proportion of resection cases differed between studies. Additionally, several studies identified less intensive oncological treatment for mGBM patients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Further, we identified that systematic differences in the diagnostic pathway impact OS outcomes, which may also explain some of the disparate findings in prior studies. Whilst the impact of an extended interval from MRI to surgery raises the possibility that this OS difference may be due to lead time bias, the difference in median interval from MRI to surgery is only 9 days, which is unlikely to be the defining difference.\u003c/p\u003e\u003cp\u003eGiven the OS difference identified, we suggest routinely collecting information on molecular vs histological diagnosis of glioblastoma for trial participants and considering stratifying for mGBM vs hGBM at trial entry, given the risk that potentially important survival improvements may be obscured by imbalances in patients between treatment arms.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eLimitations:\u003c/h2\u003e\u003cp\u003eA limitation of this study is that including patients diagnosed during 2021 meant that some centres were experiencing ongoing SARS-COV2 related pressures[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], including centres with reduced surgical capacity leading to a 50% reduction in the number of pathologically confirmed glioblastoma patients (personal communication). The exclusion of poor prognostic patients may have led to an improvement in OS. However, the reported PFS and OS for hGBM patients are in keeping with previously published results[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], suggesting that SARS-COV2 related adjustments had limited influence on survival in this cohort.\u003c/p\u003e\u003cp\u003eFurther, WHO CNS 5 was published in June 2021[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], although cIMPACT-NOW update 3 was published in 2018[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, most centres were not performing routine molecular testing for all (n\u0026thinsp;=\u0026thinsp;36 centres) or any (n\u0026thinsp;=\u0026thinsp;9 centres) glioblastoma patients, which may have led to an under-diagnosis of mGBM in this study. However, similar proportions of mGBM patients were identified at centres with complete molecular testing (8.7%) and the whole cohort (8.4%) providing confidence in this estimate. However, we would encourage comprehensive molecular testing as ~\u0026thinsp;10\u0026ndash;21% of mGBM patients would be missed by only assessing pTERT. Additionally, the small numbers of mGBM patients compared to hGBM limits the power of subgroup analyses, potentially obscuring true differences.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, we present a comparison of mGBM and hGBM patients diagnosed according to WHO CNS 5 using a large real-world cohort. We demonstrate that glioblastoma patients diagnosed according to molecular features, are uncommon (\u0026lt;\u0026thinsp;10%), and differ compared to those diagnosed based on classical histological criteria. We also identify that mGBM patients had longer OS than hGBM patients following resection with implications for clinical decision making, prognostic estimates given to patients, and clinical trial enrolment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest:\u003c/h2\u003e\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eDr Stephen David Robinson is funded by a University Hospitals Sussex NHS Foundation Trust Medical Doctoral Fellowship. Dr Sarah Kingdon is currently supported by the Tessa Jowell Brain Cancer Mission Fellowship Programme, funded by Beatson Cancer Charity, NHS Lothian Charity, and the Chief Scientist Office. Mr Ciaran Scott Hill is funded by the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre. These funders had no involvement in the design or conduct of the study. \u003cem\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/em\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e1 guarantor of integrity of the entire study: S.D.R. and G.C.; 2 study concepts and design: S.D.R., E.C. and G.C.; 3 literature research: S.D.R.; 4 clinical studies: S.D.R, S.K., S.T.W, G.C. and Histo-Mol GBM Collaborative; 5 experimental studies / data analysis: NA; 6 statistical analysis: S.D.R.; 7 manuscript preparation: S.D.R.; 8 manuscript editing: S.K., S.T.W, C.S.H., M.W., E.C., G.C. and Histo-Mol GBM Collaborative.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank Duncan Fatz and Vittorio Trevitt for their invaluable support with REDCap. We would also like to thank everyone who supported with patient identification and data management at each of the participating centres.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe summary data generated during the current study are available from the corresponding author on reasonable request. The complete data are not available due to patient confidentiality.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLouis DN, Aldape K, Brat DJ, Capper D, Ellison DW, Hawkins C, Paulus W, Perry A, Reifenberger G, Figarella-Branger D, Wesseling P, Batchelor TT, Cairncross JG, Pfister SM, Rutkowski S, Weller M, Wick W, von Deimling A (2017) Announcing cIMPACT-NOW: the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy. 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BMJ Open 10:e040898. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2020-040898\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2020-040898\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFountain DM, Piper RJ, Poon MTC, Solomou G, Brennan PM, Chowdhury YA, Colombo F, Elmoslemany T, Ewbank FG, Grundy PL, Hasan MT, Hilling M, Hutchinson PJ, Karabatsou K, Kolias AG, McSorley NJ, Millward CP, Phang I, Plaha P, Price SJ, Rominiyi O, Sage W, Shumon S, Silva IL, Smith SJ, Surash S, Thomson S, Lau JY, Watts C, Jenkinson MD (2021) British Neurosurgical Trainee Research C CovidNeuroOnc: A UK multicenter, prospective cohort study of the impact of the COVID-19 pandemic on the neuro-oncology service. Neurooncol Adv 3: vdab014 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/noajnl/vdab014\u003c/span\u003e\u003cspan address=\"10.1093/noajnl/vdab014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 192px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 360px;\"\u003e\n \u003cp\u003eUnmatched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 372px;\"\u003e\n \u003cp\u003ePSM matched\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003emGBM\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003ehGBM\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eSMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003emGBM\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003ehGBM\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 93px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eSMD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eN=75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eN=1753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eN=75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eN=67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 924px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePatient Factors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eGender:\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48 (64.0%)\u003c/p\u003e\n \u003cp\u003e27 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1114 (63.5%)\u003c/p\u003e\n \u003cp\u003e639 (36.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48 (64.0%)\u003c/p\u003e\n \u003cp\u003e27 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e44 (65.7%)\u003c/p\u003e\n \u003cp\u003e23 (34.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eAge (years):\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003cp\u003e24-87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003cp\u003e18-88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003cp\u003e24-87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003cp\u003e24-83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eWHO PS at diagnosis:\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (42.7%)\u003c/p\u003e\n \u003cp\u003e30 (40.0%)\u003c/p\u003e\n \u003cp\u003e6 (8.0%)\u003c/p\u003e\n \u003cp\u003e2 (2.7%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e498 (28.4%)\u003c/p\u003e\n \u003cp\u003e700 (39.9%)\u003c/p\u003e\n \u003cp\u003e244 (13.9%)\u003c/p\u003e\n \u003cp\u003e63 (3.6%)\u003c/p\u003e\n \u003cp\u003e12 (0.7%)\u003c/p\u003e\n \u003cp\u003e236 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (42.7%)\u003c/p\u003e\n \u003cp\u003e30 (40.0%)\u003c/p\u003e\n \u003cp\u003e6 (8.0%)\u003c/p\u003e\n \u003cp\u003e2 (2.7%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (18.0%)\u003c/p\u003e\n \u003cp\u003e36 (53.7%)\u003c/p\u003e\n \u003cp\u003e11 (16.4%)\u003c/p\u003e\n \u003cp\u003e5 (7.5%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.581\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eWHO PS at diagnosis:\u003c/p\u003e\n \u003cp\u003e0-1\u003c/p\u003e\n \u003cp\u003e2+\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62 (82.7%)\u003c/p\u003e\n \u003cp\u003e8 (10.7%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1198 (68.3%)\u003c/p\u003e\n \u003cp\u003e319 (18.2%)\u003c/p\u003e\n \u003cp\u003e236 (13.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62 (82.7%)\u003c/p\u003e\n \u003cp\u003e8 (10.7%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48 (71.6%)\u003c/p\u003e\n \u003cp\u003e16 (23.9%)\u003c/p\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.424\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Seizure:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31 (41.3%)\u003c/p\u003e\n \u003cp\u003e44 (58.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e451 (25.7%)\u003c/p\u003e\n \u003cp\u003e1302 (74.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31 (41.3%)\u003c/p\u003e\n \u003cp\u003e44 (58.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39 (58.2%)\u003c/p\u003e\n \u003cp\u003e28 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.045\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.340\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Motor:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (21.3%)\u003c/p\u003e\n \u003cp\u003e59 (78.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e667 (38.0%)\u003c/p\u003e\n \u003cp\u003e1086 (62.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (21.3%)\u003c/p\u003e\n \u003cp\u003e59 (78.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (19.4%)\u003c/p\u003e\n \u003cp\u003e54 (80.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Sensory:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (21.3%)\u003c/p\u003e\n \u003cp\u003e59 (78.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e194 (11.1%)\u003c/p\u003e\n \u003cp\u003e1559 (88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (21.3%)\u003c/p\u003e\n \u003cp\u003e59 (78.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (19.4%)\u003c/p\u003e\n \u003cp\u003e54 (80.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Speech:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (14.7%)\u003c/p\u003e\n \u003cp\u003e64 (85.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e510 (29.1%)\u003c/p\u003e\n \u003cp\u003e1243 (70.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (14.7%)\u003c/p\u003e\n \u003cp\u003e64 (85.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (19.4%)\u003c/p\u003e\n \u003cp\u003e54 (80.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Cognition:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (10.7%)\u003c/p\u003e\n \u003cp\u003e67 (89.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e475 (27.1%)\u003c/p\u003e\n \u003cp\u003e1278 (72.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (10.7%)\u003c/p\u003e\n \u003cp\u003e67 (89.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (25.4%)\u003c/p\u003e\n \u003cp\u003e50 (74.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.473\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Behaviour:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003cp\u003e71 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e134 (7.6%)\u003c/p\u003e\n \u003cp\u003e1619 (92.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003cp\u003e71 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (6.0%)\u003c/p\u003e\n \u003cp\u003e63 (94.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Visual:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003cp\u003e70 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e168 (9.6%)\u003c/p\u003e\n \u003cp\u003e1585 (90.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003cp\u003e70 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8 (11.9%)\u003c/p\u003e\n \u003cp\u003e59 (88.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Headache:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (20.0%)\u003c/p\u003e\n \u003cp\u003e60 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e600 (34.2%)\u003c/p\u003e\n \u003cp\u003e1153 (65.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (20.0%)\u003c/p\u003e\n \u003cp\u003e60 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (37.3%)\u003c/p\u003e\n \u003cp\u003e42 (62.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.430\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Reduced GCS:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (2.7%)\u003c/p\u003e\n \u003cp\u003e73 (97.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e75 (4.3%)\u003c/p\u003e\n \u003cp\u003e1678 (95.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (2.7%)\u003c/p\u003e\n \u003cp\u003e73 (97.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003cp\u003e66 (98.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom - Incidental:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003cp\u003e71 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23 (1.3%)\u003c/p\u003e\n \u003cp\u003e1730 (98.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003cp\u003e71 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e67 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Other:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (20.0%)\u003c/p\u003e\n \u003cp\u003e60 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e236 (13.5%)\u003c/p\u003e\n \u003cp\u003e1517 (86.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (20.0%)\u003c/p\u003e\n \u003cp\u003e60 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (17.9%)\u003c/p\u003e\n \u003cp\u003e55 (82.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eCorticosteroids at diagnosis:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43 (57.3%)\u003c/p\u003e\n \u003cp\u003e30 (40.0%)\u003c/p\u003e\n \u003cp\u003e2 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1392 (79.4%)\u003c/p\u003e\n \u003cp\u003e322 (18.4%)\u003c/p\u003e\n \u003cp\u003e39 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43 (57.3%)\u003c/p\u003e\n \u003cp\u003e30 (40.0%)\u003c/p\u003e\n \u003cp\u003e2 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56 (83.6%)\u003c/p\u003e\n \u003cp\u003e11 (17.9%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.498\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eAnti-epileptic drugs at diagnosis:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e45 (60.0%)\u003c/p\u003e\n \u003cp\u003e29 (38.7%)\u003c/p\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e780 (44.5%)\u003c/p\u003e\n \u003cp\u003e960 (54.8%)\u003c/p\u003e\n \u003cp\u003e13 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e45 (60.0%)\u003c/p\u003e\n \u003cp\u003e29 (38.7%)\u003c/p\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55 (82.1%)\u003c/p\u003e\n \u003cp\u003e12 (17.9%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.433\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 924px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTumour Factors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eTumour Location:\u003c/p\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003cp\u003eMidline/bilateral\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39 (52.0%)\u003c/p\u003e\n \u003cp\u003e31 (41.3%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e788 (45.0%)\u003c/p\u003e\n \u003cp\u003e868 (49.5%)\u003c/p\u003e\n \u003cp\u003e95 (5.4%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39 (52.0%)\u003c/p\u003e\n \u003cp\u003e31 (41.3%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35 (52.2%)\u003c/p\u003e\n \u003cp\u003e29 (43.3%)\u003c/p\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eTumour Location*:\u003c/p\u003e\n \u003cp\u003eFrontal\u003c/p\u003e\n \u003cp\u003eParietal\u003c/p\u003e\n \u003cp\u003eTemporal\u003c/p\u003e\n \u003cp\u003eOccipital\u003c/p\u003e\n \u003cp\u003eCerebellum\u003c/p\u003e\n \u003cp\u003eBrainstem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (33.3%)\u003c/p\u003e\n \u003cp\u003e33 (44.0%)\u003c/p\u003e\n \u003cp\u003e37 (49.3%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003cp\u003e3 (4.0%)\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e653 (37.3%)\u003c/p\u003e\n \u003cp\u003e530 (30.3%)\u003c/p\u003e\n \u003cp\u003e754 (43.0%)\u003c/p\u003e\n \u003cp\u003e157 (9.0%)\u003c/p\u003e\n \u003cp\u003e22 (1.3%)\u003c/p\u003e\n \u003cp\u003e42 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.045\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.298\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.247\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (33.3%)\u003c/p\u003e\n \u003cp\u003e33 (44.0%)\u003c/p\u003e\n \u003cp\u003e37 (49.3%)\u003c/p\u003e\n \u003cp\u003e5 (6.7%)\u003c/p\u003e\n \u003cp\u003e3 (4.0%)\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22 (32.8%)\u003c/p\u003e\n \u003cp\u003e27 (40.3%)\u003c/p\u003e\n \u003cp\u003e30 (44.8%)\u003c/p\u003e\n \u003cp\u003e10 (14.9%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e3 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.950\u003c/p\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMultifocal/multicentric tumour:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (37.3%)\u003c/p\u003e\n \u003cp\u003e47 (62.7%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e423 (24.1%)\u003c/p\u003e\n \u003cp\u003e1328 (75.8%)\u003c/p\u003e\n \u003cp\u003e2 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.308\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (37.3%)\u003c/p\u003e\n \u003cp\u003e47 (62.7%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (28.4%)\u003c/p\u003e\n \u003cp\u003e48 (71.6%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eContrast enhancing on MRI:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e54 (72.0%)\u003c/p\u003e\n \u003cp\u003e20 (26.7%)\u003c/p\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1667 (95.1%)\u003c/p\u003e\n \u003cp\u003e64 (3.7%)\u003c/p\u003e\n \u003cp\u003e22 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.236\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e54 (72.0%)\u003c/p\u003e\n \u003cp\u003e20 (26.7%)\u003c/p\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e66 (98.5%)\u003c/p\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.571\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eGrade:\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003eUnknown/Ungraded\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e1688 (96.3%)\u003c/p\u003e\n \u003cp\u003e65 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.659\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e67 (100%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.992\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMolecular markers \u0026ndash; pTERT\u003csup\u003e#\u003c/sup\u003e:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eNot tested\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e59 (89.4%)\u003c/p\u003e\n \u003cp\u003e7 (10.6%)\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e507 (78.4%)\u003c/p\u003e\n \u003cp\u003e140 (21.6%)\u003c/p\u003e\n \u003cp\u003e1075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.107\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e59 (89.4%)\u003c/p\u003e\n \u003cp\u003e7 (10.6%)\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52 (91.2%)\u003c/p\u003e\n \u003cp\u003e5 (8.8%)\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMolecular markers \u0026ndash; EGFR\u003csup\u003e#\u003c/sup\u003e:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eNot tested\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (42.4%)\u003c/p\u003e\n \u003cp\u003e38 (67.9%)\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e240 (37.3%)\u003c/p\u003e\n \u003cp\u003e403 (62.7%)\u003c/p\u003e\n \u003cp\u003e1060\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (42.4%)\u003c/p\u003e\n \u003cp\u003e38 (67.9%)\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (41.0%)\u003c/p\u003e\n \u003cp\u003e36 (59.0%)\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMolecular markers \u0026ndash; Chr 7+/10-\u003csup\u003e#\u003c/sup\u003e:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eNot tested\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (52.8%)\u003c/p\u003e\n \u003cp\u003e17 (47.2%)\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e87 (36.9%)\u003c/p\u003e\n \u003cp\u003e149 (63.1%)\u003c/p\u003e\n \u003cp\u003e1453\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (52.8%)\u003c/p\u003e\n \u003cp\u003e17 (47.2%)\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7 (70.0%)\u003c/p\u003e\n \u003cp\u003e3 (30.0%)\u003c/p\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.586\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eMGMT promoter methylation:\u003c/p\u003e\n \u003cp\u003eUnmethylated (0-10%)\u003c/p\u003e\n \u003cp\u003eMethylated (\u0026gt;10%)\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62 (82.7%)\u003c/p\u003e\n \u003cp\u003e13 (17.3%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1241 (70.8%)\u003c/p\u003e\n \u003cp\u003e454 (25.9%)\u003c/p\u003e\n \u003cp\u003e58 (3.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62 (82.7%)\u003c/p\u003e\n \u003cp\u003e13 (17.3%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60 (89.6%)\u003c/p\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 924px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTreatment Factors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eTime from MRI to surgery:\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e0-869\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e0-1395\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.686\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e0-869\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003cp\u003e0-1395\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eExtent of surgery:\u003c/p\u003e\n \u003cp\u003eBiopsy\u003c/p\u003e\n \u003cp\u003eResection\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52 (69.3%)\u003c/p\u003e\n \u003cp\u003e23 (30.7%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e532 (30.3%)\u003c/p\u003e\n \u003cp\u003e1214 (69.3%)\u003c/p\u003e\n \u003cp\u003e7 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.847\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52 (69.3%)\u003c/p\u003e\n \u003cp\u003e23 (30.7%)\u003c/p\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39 (58.2%)\u003c/p\u003e\n \u003cp\u003e28 (41.8%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eTime from surgery to radiotherapy:\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003cp\u003e12-108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e9-245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.381\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003cp\u003e12-108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003cp\u003e22-115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.406\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eOncological treatment:\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003eTemozolomide\u003c/p\u003e\n \u003cp\u003eHypofractionated RT\u003c/p\u003e\n \u003cp\u003eHypofractionated CRT\u003c/p\u003e\n \u003cp\u003eConventional CRT\u003c/p\u003e\n \u003cp\u003eOther treatments\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (20.0%)\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003cp\u003e8 (10.7%)\u003c/p\u003e\n \u003cp\u003e10 (13.3%)\u003c/p\u003e\n \u003cp\u003e31 (41.3%)\u003c/p\u003e\n \u003cp\u003e7 (9.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e374 (21.3%)\u003c/p\u003e\n \u003cp\u003e49 (2.8%)\u003c/p\u003e\n \u003cp\u003e196 (11.2%)\u003c/p\u003e\n \u003cp\u003e225 (12.8%)\u003c/p\u003e\n \u003cp\u003e752 (42.9%)\u003c/p\u003e\n \u003cp\u003e157 (9.0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15 (20.0%)\u003c/p\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003cp\u003e8 (10.7%)\u003c/p\u003e\n \u003cp\u003e10 (13.3%)\u003c/p\u003e\n \u003cp\u003e31 (41.3%)\u003c/p\u003e\n \u003cp\u003e7 (9.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14 (20.9%)\u003c/p\u003e\n \u003cp\u003e6 (9.0%)\u003c/p\u003e\n \u003cp\u003e8 (11.9%)\u003c/p\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003cp\u003e31 (46.3%)\u003c/p\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cem\u003eOncological treatment:\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSurgery only\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eIntermediate\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAggressive\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e15 (20.0%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e19 (25.3%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e41 (54.7%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e374 (21.3%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e402 (22.9%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e977 (55.7%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.880\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.003\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e15 (20.0%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e19 (25.3%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e41 (54.7%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e14 (20.9%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e15 (22.4%)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e38 (56.7%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.919\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.014\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 924px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eProgression factors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eConfirmed progression:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57 (76.0%)\u003c/p\u003e\n \u003cp\u003e18 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1294 (75.5%)\u003c/p\u003e\n \u003cp\u003e420 (24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57 (76.0%)\u003c/p\u003e\n \u003cp\u003e18 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e50 (76.9%)\u003c/p\u003e\n \u003cp\u003e15 (23.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eReceived 2\u003csup\u003end\u003c/sup\u003e line treatment:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (49.1%)\u003c/p\u003e\n \u003cp\u003e29 (50.9%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e546 (42.2%)\u003c/p\u003e\n \u003cp\u003e748 (57.8%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e28 (49.1%)\u003c/p\u003e\n \u003cp\u003e29 (50.9%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (54.0%)\u003c/p\u003e\n \u003cp\u003e23 (46.0%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 924px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurvival/Follow up\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003ePatient surviving:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (14.7%)\u003c/p\u003e\n \u003cp\u003e64 (85.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e225 (12.8%)\u003c/p\u003e\n \u003cp\u003e1528 (87.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (14.7%)\u003c/p\u003e\n \u003cp\u003e64 (85.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10 (14.9%)\u003c/p\u003e\n \u003cp\u003e57 (85.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 192px;\"\u003e\n \u003cp\u003eLength of follow up:\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003e95% confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33.8 months\u003c/p\u003e\n \u003cp\u003e29.7 \u0026ndash; 37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34.2 months\u003c/p\u003e\n \u003cp\u003e33.1 \u0026ndash; 35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33.8 months\u003c/p\u003e\n \u003cp\u003e29.7 \u0026ndash; 37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30.9 months\u003c/p\u003e\n \u003cp\u003e23.5 \u0026ndash; 38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1. Comparison of patient, tumour, treatment, progression and follow up characteristics between molecular glioblastoma patients and histological glioblastoma patients with the significant features highlighted in \u003cstrong\u003ebold\u003c/strong\u003e. *combined percentages may exceed 100 from tumours occupying multiple lobes. # percentages and statistics calculated for tested patients only. PSM: propensity score matched; mGBM: molecular glioblastoma; hGBM, histological glioblastoma; SMD: standardised mean difference; WHO PS: World Health Organisation performance status; GCS: Glasgow Coma Score; MRI: magnetic resonance imaging; pTERT: telomerase reverse transcriptase promoter mutation; EGFR: epidermal growth factor receptor amplification; Chr 7+/10-: combined gain of chromosome 7 and loss of chromosome 10; MGMT: O6-methylguanine methyltransferase; RT: \u0026nbsp;radiotherapy alone; CRT: concurrent chemoradiotherapy; Other treatments: other oncological treatments (conventionally fractionated radiotherapy alone, palliative radiotherapy, etc\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 245px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 175px;\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003eHazard ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eHazard ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eContinuous\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.03\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.01 \u0026ndash; 1.06)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eGender:\u003c/p\u003e\n \u003cp\u003eMale vs Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresenting symptom \u0026ndash; Seizures:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.36\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.20 \u0026ndash; 0.63)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresenting symptom \u0026ndash; Motor:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.39\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.32 \u0026ndash; 4.31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.71\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.19 \u0026ndash; 6.16)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Speech:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Cognition:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresenting symptom \u0026ndash; Behaviour:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.02\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(4.02 \u0026ndash; 48.84)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresenting symptom \u0026ndash; Vision:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.61\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.02 \u0026ndash; 6.68)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Headache:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Sensory:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresenting symptom \u0026ndash; Reduced GCS:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.57\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.29 \u0026ndash; 23.99)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13.40\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(2.05 \u0026ndash; 87.41)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Incidental:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePresenting symptom \u0026ndash; Other:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eCorticosteroids at diagnosis:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAEDs at diagnosis:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.44\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.26 \u0026ndash; 0.74)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.33\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.41 \u0026ndash; 0.80)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWHO Performance status:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0-1 vs 2+\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.27\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.46 \u0026ndash; 7.56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eSite:\u003c/p\u003e\n \u003cp\u003eLeft vs Right vs Midline/Bilateral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eFrontal lobe:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eParietal lobe:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eTemporal lobe:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eOccipital lobe:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eCerebellum:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eBrainstem:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultifocal/multicentric:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNo vs Yes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.69\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.01 \u0026ndash; 2.83)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eContrast enhancing on MRI:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eGrade:\u003c/p\u003e\n \u003cp\u003e2 vs 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eMGMT methylation:\u003c/p\u003e\n \u003cp\u003eNo vs Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBiopsy vs Resection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.36\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.19 \u0026ndash; 0.67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOncological treatment:\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNone vs Intermediate vs Aggressive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.33\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.22 \u0026ndash; 0.48)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.46\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.25 \u0026ndash; 0.83)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. Univariate and multivariate Cox regression analysis for overall survival in molecular glioblastoma patients. Variables with p-value \u0026lt;0.05 on univariate analysis were chosen for assessment in the multivariate analysis with the significant features highlighted in \u003cstrong\u003ebold\u003c/strong\u003e. \u0026nbsp;95% CI: 95% confidence interval; GCS: Glasgow Coma Score; AEDs: Anti-epileptic drugs; WHO: World Health Organisation; MRI: Magnetic Resonance Imaging; MGMT: O6-methylguanine methyltransferase.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuro-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"neon","sideBox":"Learn more about [Journal of Neuro-Oncology](https://www.springer.com/journal/11060)","snPcode":"11060","submissionUrl":"https://submission.nature.com/new-submission/11060/3","title":"Journal of Neuro-Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Glioblastoma, Molecular Glioblastoma, Survival, Real-World Evidence, Histology, Classification","lastPublishedDoi":"10.21203/rs.3.rs-7401683/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7401683/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Purpose: Since the 2021 World Health Organisation (WHO) classification, glioblastoma could be diagnosed based on classical histological features (hGBM) or molecular criteria (mGBM). However, prior studies included patients who required reclassification as a mGBM, potentially biasing survival analyses. The Histo-Mol GBM collaborative performed an international multicentre retrospective real-world cohort study of glioblastoma patients diagnosed according to WHO CNS 5.\n\nMethods: We identified consecutive patients diagnosed in 2021 with IDH wildtype glioblastoma according to WHO CNS 5. Clinicopathological, treatment, and survival data were collected and compared between mGBM and hGBM.\n\nResults: 1828 patients diagnosed with glioblastoma were included. 75 mGBM patients (8.4% of tested patients) were identified, with no difference in age (median 61 vs 64, p=0.057), gender (p=0.937), or proportion with performance status 0-1 (82.7% vs 68.3%, p=0.052) compared to hGBM. mGBM patients had an extended interval from MRI to surgery (median 23 vs 14 days, p\u003c0.001) and more frequently underwent biopsy (69.3% vs 30.3%, p\u003c0.001), but equivalent proportions received oncological treatment (80.0% vs 78.7%, p=0.784). Overall survival (OS) from surgery was not different (p=0.063). However, OS from initial MRI, stratified by surgical extent, demonstrated improved OS for mGBM patients (hazard ratio (HR) 0.56, 95% confidence interval (CI): 0.43-0.73). Propensity score matching identified improved survival following resection (HR 0.48, 95% CI: 0.24-0.95; median OS: 26.0 versus 14.0 months, p=0.031) but not biopsy (HR 1.10, 95% CI: 0.71-1.72).\n\nConclusion: In this large real-world cohort, mGBMs had longer OS than hGBMs following resection with implications for prognostication and clinical decision making.","manuscriptTitle":"Understanding the difference in symptoms and outcomes between glioblastoma patients diagnosed based on histological or molecular criteria: a retrospective cohort analysis from the Histo-Mol GBM collaborative","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 09:36:47","doi":"10.21203/rs.3.rs-7401683/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-30T16:56:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T12:10:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"151704884549692482916082963846340691653","date":"2025-09-09T07:36:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T14:04:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"301131213535950414645402617459655844334","date":"2025-08-22T21:11:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-21T19:06:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-21T10:29:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-21T09:26:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Neuro-Oncology","date":"2025-08-18T16:33:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuro-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"neon","sideBox":"Learn more about [Journal of Neuro-Oncology](https://www.springer.com/journal/11060)","snPcode":"11060","submissionUrl":"https://submission.nature.com/new-submission/11060/3","title":"Journal of Neuro-Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"144c9c89-03a3-4f35-b0a0-09337c999ace","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:08:36+00:00","versionOfRecord":{"articleIdentity":"rs-7401683","link":"https://doi.org/10.1007/s11060-025-05364-8","journal":{"identity":"journal-of-neuro-oncology","isVorOnly":false,"title":"Journal of Neuro-Oncology"},"publishedOn":"2026-01-08 15:58:17","publishedOnDateReadable":"January 8th, 2026"},"versionCreatedAt":"2025-11-06 09:36:47","video":"","vorDoi":"10.1007/s11060-025-05364-8","vorDoiUrl":"https://doi.org/10.1007/s11060-025-05364-8","workflowStages":[]},"version":"v1","identity":"rs-7401683","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7401683","identity":"rs-7401683","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}