Real-World Evidence on the Management and Outcomes of Glioblastoma in Elderly Patients: A Monocentric Retrospective Analysis

Real-World Evidence on the Management and Outcomes of Glioblastoma in Elderly Patients: A Monocentric Retrospective Analysis | 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 Real-World Evidence on the Management and Outcomes of Glioblastoma in Elderly Patients: A Monocentric Retrospective Analysis Jörg Andreas Müller, Ian Schirrwagen, Clara Pitzschel, Daniel Medenwald, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8011713/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background: Glioblastoma (GBM) carries a poor prognosis, and elderly or frail patients are often underrepresented in randomized trials. This study evaluated real-world outcomes and prognostic factors in a monocentric cohort of elderly GBM patients. Methods: We retrospectively analyzed 67 patients aged ≥ 65 years with histologically confirmed GBM treated between 2014 and 2023 at a single institution. Overall survival (OS) was defined as the primary endpoint, and progression-free survival (PFS) as the secondary endpoint. Univariable and multivariable Cox proportional hazards regression models were applied to assess prognostic factors, including age, sex, Karnofsky Performance Status (KPS), extent of resection, and temozolomide (TMZ) administration. Sensitivity analyses included proportional hazards testing using Schoenfeld residuals. Results: The median OS was 7.0 months (interquartile range [IQR] 5.5–13.0), and the median PFS was 5.0 months (IQR 3.6–7.9). In multivariable analyses, increasing age was independently associated with worse OS (HR 1.07, 95% CI 1.00–1.14, p = 0.043) and PFS (HR 1.06, 95% CI 1.00–1.13, p = 0.038). Female sex was independently associated with improved OS (HR 0.50, 95% CI 0.26–0.98, p = 0.044) and PFS (HR 0.41, 95% CI 0.21–0.80, p = 0.009). Higher KPS was significantly associated with better OS (HR 0.98, 95% CI 0.96–1.00, p = 0.064) and PFS (HR 0.98, 95% CI 0.95–1.00, p = 0.024). Omission of TMZ predicted inferior OS (HR 2.41, 95% CI 1.24–4.66, p = 0.009) and PFS (HR 2.31, 95% CI 1.20–4.46, p = 0.013). Total resection was independently associated with improved OS (HR 0.50, 95% CI 0.26–0.96, p = 0.037), while showing a non-significant trend for PFS (HR 0.62, 95% CI 0.33–1.17, p = 0.14). Sensitivity analyses confirmed the robustness of the models, with no relevant violations of the proportional hazards assumption (global p = 0.164 for OS; p = 0.086 for PFS). Conclusions: In this real-world cohort of elderly GBM patients, survival outcomes remained poor despite multimodal therapy. Independent predictors of improved outcomes included younger age, female sex, higher performance status, total resection, and temozolomide therapy. Sensitivity analyses confirmed the robustness of the models, underscoring the prognostic relevance of established clinical and treatment-related factors and highlighting the need for individualized treatment approaches in this vulnerable population. glioblastoma elderly survival temozolomide chemoradiotherapy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Malignant primary brain tumors, though relatively rare with an annual incidence of approximately 7 per 100,000 individuals, remain among the most devastating cancers, causing more than 15,000 deaths per year in the United States [ 1 ]. Glioblastoma (GBM) (WHO grade IV) represents nearly half of all malignant brain tumors and carries a particularly poor prognosis, with a five-year survival rate of only about 6–7% [ 1 ]. GBMs are traditionally divided into primary and secondary forms. Primary GBMs arise de novo, typically in older patients, whereas secondary GBMs develop from lower-grade diffuse astrocytomas and more often occur in younger individuals. Although histologically indistinguishable, these entities differ in their molecular profiles and clinical outcomes [ 2 ]. The growing importance of molecular diagnostics is also reflected in the 2021 WHO Classification of Central Nervous System Tumors, which emphasizes integrated histological and molecular diagnoses [ 3 ]. These developments highlight the heterogeneity of GBM. In addition to histopathological features, molecular markers such as IDH mutation status, TERT promoter mutations, and 1p/19q codeletion have emerged as critical classifiers. On the basis of these alterations, gliomas can be stratified into distinct molecular groups that differ in age at onset, clinical behavior, survival, and underlying genetic susceptibility, underscoring their distinct mechanisms of pathogenesis [ 4 , 5 ]. Epigenetic alterations also play a crucial role in GBM biology and treatment response. In particular, methylation of the MGMT promoter has been shown to predict benefit from alkylating agents such as temozolomide (TMZ) and is an independent favorable prognostic factor [ 6 ]. The current standard of care consists of maximal safe surgical resection followed by combined radiotherapy (RT) and TMZ, which significantly improves survival compared with RT alone [ 1 , 7 ]. Additional treatment modalities have been investigated to further improve outcomes. Tumor Treating Fields (TTFields), a non-invasive antimitotic therapy, demonstrated a significant prolongation of both progression-free and overall survival when added to maintenance TMZ in patients with newly diagnosed GBM, with a manageable toxicity profile primarily consisting of mild skin reactions [ 8 ]. The vascular endothelial growth factor (VEGF) inhibitor bevacizumab, although widely used in recurrent disease, has not been shown to improve overall survival (OS) on a population level, despite potential benefits such as reduced corticosteroid dependence [ 9 ]. Retrospective and registry-based studies confirm the benefit of the Stupp protocol, with OS and PFS compared with pre-2004 cohorts, and have highlighted the potential role of second-line chemotherapy and radiosurgery at recurrence [ 10 ]. In elderly patients, therapeutic strategies require further adaptation due to limited tolerance to intensive treatment. Randomized trials have demonstrated that RT provides a modest survival benefit compared with supportive care alone, without impairing quality of life [ 11 ]. Moreover, hypofractionated RT regimens are non-inferior to conventional RT and offer advantages such as reduced treatment duration and lower corticosteroid requirements [ 12 ]. The addition of TMZ to short-course RT significantly prolongs survival, particularly in patients with MGMT promoter methylation [ 13 ]. Similarly, randomized evidence supports both TMZ monotherapy and hypofractionated RT as reasonable treatment options in patients over 70 years, with MGMT methylation status serving as a predictive biomarker for treatment benefit [ 14 ]. While randomized clinical trials have defined the current standard of care for GBM, their strict eligibility criteria often exclude elderly patients, individuals with comorbidities, or those with poor performance status. Consequently, outcomes reported in these studies may not fully reflect the reality of daily clinical practice. In contrast, real-world data provide valuable insights into treatment patterns, prognostic factors, and survival outcomes across unselected and heterogeneous patient populations. Against this background, the aim of the present study is to analyze real-world outcomes of GBM patients treated at our institution in a monocentric, retrospective cohort, thereby complementing clinical trial evidence and contributing to a more comprehensive understanding of GBM care in routine practice. Methods Data and material Patient recruitment was conducted retrospectively using the digital archives of the Department of Radiation Oncology at University Hospital Halle (Saale). Data were anonymized and extracted from the hospital information system ORBIS (version 03.20.02.01). Imaging diagnostics and RT data were obtained from Centricity PACS (GE Healthcare) and Elekta Mosaiq (version 2.84). All patients with histologically confirmed GBM (WHO grade IV) who received treatment between 2014 and 2023 were considered. The date of tumor progression was either obtained from the interdisciplinary tumor board documentation or derived from follow-up MRI imaging. The study received a positive vote and was approved by the ethics committee of the Medical Faculty of Martin Luther University Halle-Wittenberg (2024-002). Clinical variables were categorized for statistical analysis. Age at diagnosis was recorded as a continuous variable (mean and range). Elderly status was defined as an age of ≥ 65 years at the time of diagnosis. Sex was classified as male or female. Performance status was assessed using the Karnofsky Performance Status (KPS, reported as median and range) and, where available, the ECOG performance status. Molecular profiles included MGMT promoter methylation status, IDH mutation status, TERT mutation, and EGFR amplification/mutation. The extent of resection was classified according to the EOR classification as gross total resection, near total resection, subtotal resection, or biopsy. Postoperative MRI within 48–72 hours after surgery was evaluated for the presence of residual tumor (reported as percentage of patients with radiological evidence of tumor remnant). Primarily radiologic evaluation was used for the evaluation of tumor residual status. RT parameters included fractionation scheme (normofractionated, hypofractionated, ultrahypofractionated), total dose (median, mean, range), dose per fraction, and overall treatment time. RT was considered complete if the full prescribed course was delivered. Chemotherapy with TMZ was recorded as a binary variable (yes/no) and further specified as concomitant and/or sequential administration. Additional variables included applied dose and the number of treatment cycles. Dexamethasone use was documented at treatment initiation and at the end of therapy (dosage in mg). Tumor site was classified by anatomical location (frontal, temporal, parietal, occipital, cerebellar, corpus callosum, brainstem, pons, deep white matter) and reported as percentage distribution. Tumor volumes were assessed as gross tumor volume (GTV and GTV recurrence) and clinical target volume (CTV and CTV recurrence), reported as mean, median, and standard deviation in cm³. Progression was categorized as in-field or out-of-field recurrence and summarized as percentage distribution. Statistical analyses The primary endpoint of this study was overall survival (OS), while progression-free survival (PFS) was defined as the secondary endpoint. PFS and OS were calculated from the end of RT. PFS was defined as the time from the last day of radiotherapy to the date of radiologically or clinically confirmed tumor progression or death from any cause, whichever occurred first. OS was defined as the time from the last day of radiotherapy to death from any cause. Patients without an event were censored at the date of last follow-up. To evaluate the association between clinical and treatment-related parameters and survival outcomes, Cox proportional hazards regression models were applied. In a first step, univariable Cox regression analyses were performed including the following covariates: age, sex, performance status (Karnofsky Performance Status [KPS], extent of resection (total resection vs. other) and the administration of TMZ (yes vs. no). Gross tumor volume (GTV) and molecular markers were explored in preliminary models but were not retained for final analysis due to limited data availability and lack of statistical significance. All variables that reached statistical significance in the univariable analyses were subsequently included in the multivariable Cox regression model. The results were expressed as hazard ratios (HR) with 95% confidence intervals (CI), and a p-value < 0.05 was considered statistically significant. To ensure the robustness of the findings, sensitivity analyses were performed. These included adjustment for the updated WHO 2021 glioma classification, as well as stratified analyses according to the main clinical predictors (age, sex, KPS, extent of resection, and TMZ use). Model diagnostics were performed by plotting Schoenfeld residuals to evaluate model fit and formally testing the proportional hazards assumption. Kaplan–Meier survival curves were generated to illustrate OS and PFS in the entire cohort and to visualize differences between clinically relevant subgroups. Stratified analyses were presented according to age (< 70 vs. ≥70 years), sex, KPS (< 70% vs. ≥70%), extent of resection (total resection vs. other), and TMZ treatment (yes vs. no). All statistical analyses were conducted using RStudio, version 2024.04.2 + 764. During the preparation of this work, the authors used ChatGPT, a language model developed by OpenAI Inc., to improve writing style and check grammar and spelling. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the final manuscript. Results Patient characteristics A total of n=67 patients with histologically confirmed glioblastoma (GBM) were included in the analysis (Table 1). The median age at diagnosis was 73.7 years (range 65–88 years). Thirty-seven patients (55%) were male and 30 patients (45%) were female. The median Karnofsky Performance Status (KPS) at baseline was 60% (range 30–100%), with data missing for five patients. With respect to molecular markers, MGMT promoter status was methylated in 36 patients (54%), unmethylated in 24 patients (36%), and unknown in 7 patients (10%). IDH mutation was not observed; 56 patients (84%) had wild-type status, and 11 patients (16%) had unknown status. Regarding surgical treatment, 28 patients (42%) underwent gross total resection, 17 patients (25%) near-total resection, 2 patients (3%) subtotal resection, and 16 patients (24%) biopsy, while 4 patients (6%) had missing information on resection status. RT was delivered as normofractionated treatment in 15 patients (22%), hypofractionated in 43 patients (64%), and ultrahypofractionated in 9 patients (13%). The median total dose was 40 Gy (range 5–60 Gy). Concomitant or sequential chemotherapy with temozolomide (TMZ) was administered in 42 patients (63%), while 25 patients (37%) did not receive TMZ. Volumetric data were available for most patients. The mean gross tumor volume (GTV) was 205 cm³ (median 40 cm³, maximum 1,201 cm³; missing in 7 patients), and the mean clinical target volume (CTV) was 149 cm³ (median 142 cm³, Q1 = 75; missing in 24 patients). Patterns of recurrence could be classified in 17 patients (25%), with 3 in-field (4.6%) and 14 out-of-field (22%) recurrences, while the majority (n = 50; 75%) had missing or indeterminate data. Radiologic evidence of residual tumor after surgery was reported in 37 patients (55%), absent in 18 patients (27%), and unknown in 12 patients (18%). Treatment with tumor treating fields (TTF) was initiated in 6 patients (9%), whereas 55 patients (82%) did not receive TTF therapy. In an additional 6 patients (9%), information on TTF use was missing. A complete overview of all patient characteristics, including detailed comorbidities and supportive treatment data, is provided in Table S1 . When comparing baseline characteristics between male and female patients, no statistically significant age difference was observed (median 73.0 vs. 74.0 years, p = 0.082). However, women presented with a significantly lower median Karnofsky Performance Status (KPS) compared to men (60% vs. 70%, p = 0.021). With respect to molecular markers, MGMT promoter methylation differed significantly between sexes (p = 0.019). A higher proportion of female patients had methylated MGMT promoter status (67% vs. 43%), while unmethylated status was more frequent among men (38% vs. 33%), and MGMT status was unknown in 19% of male but in none of the female patients. No significant differences were found between men and women regarding radiotherapy regimen (p = 0.6) or surgical resection status (p = 0.2). The distribution of radiotherapy schemes was comparable, with hypofractionated regimens being most common in both groups (59% in men vs. 70% in women). A trend toward more frequent omission of temozolomide (TMZ) in female patients was observed (50% vs. 27% in men, p = 0.076). Table 1. Baseline clinical, molecular, and treatment characteristics of patients with GBM. Characteristic N = 67 1 Age 73.7 (65.0, 88.0) Gender male 37 (55%) female 30 (45%) Karnofsky-Index [%] 60 (30, 100) Unknown 5 MGMT-status unmethylated 24 (36%) methylated 36 (54%) unknown 7 (10%) IDH wild-type 56 (84%) unkown 11 (16%) Resection status (EOR classification) Gross total resection 28 (42%) Near total resection 17 (25%) Subtotal resection 2 (3.0%) Biospy 16 (24%) Unknown 4 (6.0%) Radiotherapy - scheme normofractionated 15 (22%) hypofractionated 43 (64%) ultrahypofrationated 9 (13%) Total Dose [Gy] 40 (5, 60) Temozolomide no 25 (37%) yes 42 (63%) GTV [cm³] 205, 40, 1,201 Unknown 7 CTV [cm³] 149, 142, 75 Unknown 24 Recurrence In-field 3 (4.6%) Out-field 14 (22%) unknown 50 (75%) Radiology showing rest of malignoma no 18 (27%) yes 37 (55%) unknwon 12 (18%) TTF-treatment no 55 (82%) yes 6 (9.0%) unknown 6 (9.0%) 1 Mean (Min, Max); n (%); Median (Min, Max); Median (Q1, Q3); Mean, Median, SD Survival analyses In the entire cohort of 71 patients, the median OS was 7.0 months (interquartile range [IQR] 5.5–13.0 months), with 25% of patients surviving less than 3.2 months and 25% surviving longer than 23 months. When stratified by MGMT promoter methylation status, patients with methylated tumors had a median OS of 8.1 months (IQR 5.3–21.0 months), with the 25th and 75th percentiles at 4.9 and 24.0 months, respectively. In contrast, patients with unmethylated tumors showed a median OS of 8.8 months (IQR 5.5–23.0 months), with the 25th and 75th percentiles at 3.6 and 23.0 months, respectively. Among male patients, overall survival (OS) at six months was highest in the normofractionated group (73.3%), followed by hypofractionated RT (58.1%) and ultrahypofractionated RT (22.2%). At twelve months, OS rates declined to 60.0%, 37.2%, and 0.0%, respectively. Progression-free survival (PFS) showed a similar trend, with six-month PFS of 53.3% (normofractionated), 43.4% (hypofractionated), and 11.1% (ultrahypofractionated), and corresponding twelve-month rates of 40.0%, 26.5%, and 0.0%. Among female patients, survival outcomes were overall lower compared to men. Six-month OS rates were 60.0% for normofractionated, 50.0% for hypofractionated, and 25.0% for ultrahypofractionated RT, while twelve-month OS rates were 40.0%, 28.6%, and 0.0%, respectively. For PFS, six-month rates were 65.0%, 55.0%, and 33.0%, declining to 50.0%, 30.0%, and 0.0% at twelve months. In univariable Cox regression analyses, increasing age was significantly associated with worse OS (HR 1.08, 95% CI 1.02–1.13, p = 0.004). Female sex was not significantly associated with OS in the univariable model (HR 0.83, 95% CI 0.50–1.37, p = 0.50). A higher KPS was significantly associated with better prognosis (HR 0.98, 95% CI 0.96–0.99, p = 0.006). Omission of TMZ was strongly associated with inferior survival (HR 2.65, 95% CI 1.53–4.59, p < 0.001). Regarding resection status, total resection showed a trend toward improved OS compared to other resection types (HR 0.59, 95% CI 0.33–1.07, p = 0.074). In the multivariable Cox regression model, age remained independently associated with worse OS (HR 1.07, 95% CI 1.00–1.14, p = 0.043). Female sex emerged as an independent prognostic factor for improved survival (HR 0.50, 95% CI 0.26–0.98, p = 0.044). Omission of TMZ remained a strong predictor of inferior survival (HR 2.41, 95% CI 1.24–4.66, p = 0.009). Total resection was independently associated with improved OS (HR 0.50, 95% CI 0.26–0.96, p = 0.037). A higher KPS also showed a trend toward improved OS (HR 0.98, 95% CI 0.96–1.00, p = 0.064). A detailed summary of the univariable and multivariable Cox regression analyses is provided in Table 2, and Kaplan–Meier curves for OS according to relevant clinical subgroups are shown in Figures 1–4. Table 2. Results of univariable and multivariable Cox regression analyses for OS in patients with GBM. Shown are HR with corresponding 95% CI. Characteristic Univariable Multivariable HR 95% CI p-value HR 95% CI p-value Age 1.08 1.02, 1.13 0.004 1.07 1.00, 1.14 0.043 Gender 0.5 male — — — — Female 0.83 0.50, 1.37 0.50 0.26, 0.98 0.044 Temozolomide <0.001 yes — — — — no 2.65 1.53, 4.59 2.41 1.24, 4.66 0.009 Resection status 0.074 Rest — — — — total 0.59 0.33, 1.07 0.50 0.26, 0.96 0.037 Karnofsky 0.98 0.96, 0.99 0.006 0.98 0.96, 1.00 0.064 Abbreviations: CI = Confidence Interval, HR = Hazard Ratio The median PFS was 5.0 months (IQR 3.6–7.9 months), with 25% of patients progressing within 2.3 months and 25% remaining progression-free for more than 13 months. When stratified by MGMT promoter methylation status, patients with methylated tumors had a median PFS of 5.3 months (IQR 3.6–14.0 months), with the 25th and 75th percentiles at 2.6 and 17.0 months, respectively. Patients with unmethylated tumors had a median PFS of 5.6 months (IQR 3.2–10.0 months), with the 25th and 75th percentiles at 2.8 and 10.0 months, respectively. In univariable Cox regression analyses, age was significantly associated with shorter PFS (HR 1.06, 95% CI 1.01–1.11, p = 0.019). Female sex was not significantly associated with PFS (HR 0.72, 95% CI 0.43–1.20, p = 0.20). Omission of temozolomide (TMZ) was significantly associated with worse PFS (HR 2.40, 95% CI 1.37–4.20, p = 0.003). Total resection showed a non-significant trend toward better PFS compared to non-total resection (HR 0.62, 95% CI 0.34–1.12, p = 0.10). A higher Karnofsky Performance Status (KPS) was significantly associated with improved PFS (HR 0.97, 95% CI 0.96–0.99, p = 0.004). In the multivariable Cox regression model, age remained significantly associated with shorter PFS (HR 1.06, 95% CI 1.00–1.13, p = 0.038). Female sex was independently associated with better PFS (HR 0.41, 95% CI 0.21–0.80, p = 0.009). Lack of TMZ treatment continued to be significantly associated with inferior PFS (HR 2.31, 95% CI 1.20–4.46, p = 0.013). Total resection again was not significantly associated with PFS (HR 0.62, 95% CI 0.33–1.17, p = 0.14). Higher KPS remained significantly associated with improved PFS (HR 0.98, 95% CI 0.95–1.00, p = 0.024). A detailed summary of the univariable and multivariable Cox regression analyses for PFS is presented in Table 3 . Supplementary Kaplan–Meier curves for PFS according to relevant clinical subgroups are provided in Figures 3 and S1–S4. Table 3. Results of univariable and multivariable Cox regression analyses for PFS in patients with GBM. Shown are HR with corresponding 95% CI and p-values. Characteristic Univariable Multivariable HR 95% CI p-value HR 95% CI p-value Age 1.06 1.01, 1.11 0.019 1.06 1.00, 1.13 0.038 Gender 0.2 male — — — — female 0.72 0.43, 1.20 0.41 0.21, 0.80 0.009 Temozolomide 0.003 yes — — — — no 2.40 1.37, 4.20 2.31 1.20, 4.46 0.013 Resection status 0.10 non-total — — — — total 0.62 0.34, 1.12 0.62 0.33, 1.17 0.14 Karnofsky Index 0.97 0.96, 0.99 0.004 0.98 0.95, 1.00 0.024 Abbreviations: CI = Confidence Interval, HR = Hazard Ratio Sensitivity Analyses In sensitivity analyses, the results of the multivariable models for OS and PFS remained largely consistent. Tests of the proportional hazards assumption did not indicate relevant deviations for OS (global p = 0.164) or PFS (global p = 0.086). For OS, all covariates showed stable hazard ratios over time (age p = 0.999, sex p = 0.755, KPS p = 0.160, TMZ p = 0.424, resection status p = 0.058). For PFS, a deviation from the proportional hazards assumption was observed for resection status (p = 0.010), while all other variables fulfilled the assumption (age p = 0.634, sex p = 0.792, KPS p = 0.381, TMZ p = 0.131). Inspection of Schoenfeld residual plots suggested only mild time-dependent effects for resection status in the PFS model, with no substantial violations for the remaining covariates. The corresponding Schoenfeld residual plots for the main prognostic covariates are shown in Figure S5. Given these findings, no model stratification was deemed necessary, and the main prognostic associations for both OS and PFS were considered robust. The detailed numerical results of these tests, including chi-square statistics and p-values for individual covariates as well as the global model, are summarized in Table S2 ( Tests of the proportional hazards assumption for OS and PFS in patients with glioblastoma ). Discussion In this monocentric, retrospective real-world analysis of elderly and predominantly frail patients with histologically confirmed GBM, we observed a median overall survival (OS) of 7.0 months and a median progression-free survival (PFS) of 5.0 months. Multivariable analyses identified younger age, higher performance status, total resection, and concomitant temozolomide (TMZ) as independent predictors of improved outcomes. Sensitivity and subgroup analyses confirmed the robustness of these findings, underscoring the prognostic value of established clinical and treatment-related parameters in this vulnerable patient population. Our results align with prior randomized and prospective evidence evaluating radiotherapy (RT) fractionation and chemotherapy in elderly GBM. The majority of patients (63%) received hypofractionated RT, reflecting a preference for shorter treatment courses in older populations (median age 73.6 years, median KPS 60%). The median OS of 7.0 months corresponds closely to findings by Roa et al., who reported comparable survival for 40 Gy in 15 fractions versus conventional 60 Gy schedules in patients aged ≥ 60 years, with reduced treatment burden and steroid use in the shorter regimen [ 12 ]. Similarly, Jablonska et al. prospectively investigated hypofractionated RT with concomitant TMZ in elderly patients with poor prognostic features, reporting a median OS and PFS of 7 months[ 15 ], consistent with our observations. The randomized phase III IAEA trial by Roa, Kepka et al. compared an ultra-short RT regimen (25 Gy in 5 fractions) with the standard 40 Gy in 15 fractions in elderly and frail GBM patients. Non-inferiority of the 1-week schedule was demonstrated, with median OS 7.9 vs. 6.4 months and comparable PFS (4.2 months in both arms), alongside preserved quality of life and reduced treatment burden [ 16 ]. In our cohort, 13% received ultrahypofractionated RT, reflecting the clinical adoption of this approach. The median OS of 7.0 months observed here—predominantly under hypofractionated or ultrahypofractionated schedules—is consistent with the IAEA data and supports condensed RT as a feasible option for elderly or frail GBM patients. The Nordic trial by Malmström et al. also demonstrated that both hypofractionated RT and TMZ monotherapy achieved superior survival compared with conventional RT in patients > 70 years (median OS 7.5 and 8.3 months vs. 6.0 months) [ 14 ]. Although our cohort was too small for statistical comparison of fractionation schemes, outcomes were comparable to those trials, reinforcing hypofractionation as a practical standard. More recently, Zemskova et al. retrospectively compared conventional and hypofractionated RT and found better outcomes with conventional schedules in patients with good KPS and limited disease [ 17 ]. Our findings differ, likely reflecting the older and frailer nature of our population, where hypofractionation was predominant and yielded survival comparable to prospective studies. Taken together, our results confirm the clinical suitability of hypofractionated RT, particularly when combined with TMZ and adequate resection, in elderly GBM patients. Increasing age was independently associated with worse OS and PFS, consistent with prior studies demonstrating that both chronological and biological age negatively affect survival [ 18 ]. The relatively narrow age range in our series (65–88 years) may have limited discrimination across subgroups, but the continuous association between age and prognosis persisted, emphasizing age as a relevant prognostic dimension even within older populations. Other studies have reported more nuanced results. Hallaert et al. did not confirm an independent prognostic effect of sex after adjustment for MGMT, age, and extent of resection but validated MGMT methylation as a key biomarker [ 19 ]. In our data, patients with unmethylated MGMT promoter status showed slightly longer median OS (8.8 vs. 8.1 months) and PFS (5.6 vs. 5.3 months) than those with methylated tumors, although these differences were not statistically significant. This inversion compared with prior literature likely reflects small subgroup sizes and incomplete molecular data. Overall, the influence of MGMT status was outweighed by clinical and treatment-related factors such as resection and TMZ use. Increasing age was independently associated with worse OS and PFS, consistent with prior studies demonstrating that both chronological and biological age negatively affect survival [ 18 ]. The relatively narrow age range in our series (65–88 years) may have limited discrimination across subgroups, but the continuous association between age and prognosis persisted, emphasizing age as a relevant prognostic dimension even within older populations. Recurrence classification was available for 24% of patients, with 4.6% showing in-field and 22% out-of-field progression. While most published series report predominantly local or in-field recurrences, our higher proportion of out-of-field failures likely reflects selection bias, limited follow-up imaging, and small numbers of evaluable events. Murakami et al. and Tu et al. emphasized that local control is largely determined by resection extent and GTV margin definition [ 20 , 21 ], while Zheng et al. showed that omitting peritumoral FLAIR abnormalities can safely reduce irradiated volume [ 22 ]. In line with these findings, our data suggest that local tumor control and individualized target delineation remain central to optimizing outcomes. Future work should further investigate tumor volume as a prognostic factor in elderly real-world cohorts. Murakami et al. emphasized that control of the macroscopic tumor bulk determines the length of the progression-free interval [ 20 ]. Contemporary reirradiation studies also underline the relevance of tumor volume and margin selection: Margulies et al. reported higher rates of marginal and out-of-field failures with smaller GTV-to-PTV margins (1 mm) and larger PTV volumes [ 23 ], while adaptive strategies have been shown to optimize tumor coverage and reduce normal tissue dose in the presence of tumor shrinkage or expansion [ 24 ]. Together, these data support precise, GTV-focused contouring with carefully balanced margins (as suggested by Tu and Zheng) and consideration of adaptive replanning when volumetric changes occur. Future studies should also focus on tumor volume as prognostic factor in terms of real-world outcomes. Concomitant TMZ remained a strong independent predictor of improved OS and PFS, consistent with the survival benefit demonstrated in the Stupp trial [ 7 ] and subsequent real-world analyses [ 25 ]. Patients who did not receive TMZ were older (median 76 years) and had lower KPS (median 55%), suggesting that treatment omission was largely due to frailty and comorbidity. These patients often had IDH-wildtype, MGMT-unmethylated tumors and underwent limited surgery, indicating an unfavorable biological and clinical profile. Most were treated with hypofractionated or ultrahypofractionated RT, consistent with palliative intent and reduced treatment tolerance. Only a small subset (n = 6, 9%) received tumor treating fields (TTF), precluding meaningful statistical analysis. The limited use likely reflects the advanced age, frailty, and logistical barriers inherent to TTF therapy in this population. Limitations and strengths This study’s retrospective, single-center design and modest sample size limit generalizability and increase the potential for bias. Missing molecular and volumetric data, as well as incomplete follow-up imaging, restricted detailed assessment of recurrence patterns. Nevertheless, the dataset represents unselected, real-world elderly GBM patients—an underrepresented group in clinical trials. Most patients were treated according to guideline-based standards, with adherence to combined chemoradiation regimens when feasible. Statistical robustness was supported by multivariable Cox regression and sensitivity testing using Schoenfeld residuals, which confirmed no relevant proportional hazards violations. The integration of demographic, surgical, and RT parameters provides a comprehensive perspective on prognostic factors in daily clinical practice. Conclusions In this retrospective real-world cohort of elderly patients with GBM, overall and progression-free survival remained poor despite multimodal therapy. Increasing age was independently associated with worse outcomes, whereas female sex (for PFS), higher performance status, total resection, and concomitant TMZ treatment were linked to improved survival. The majority of patients received hypofractionated or ultrahypofractionated RT, with survival outcomes comparable to those reported in prospective trials. These findings reinforce the prognostic relevance of established clinical and treatment-related factors and support the use of condensed, evidence-based treatment schedules in the management of elderly and frail GBM patients. Abbreviations CI: Confidence Interval CRT: Chemoradiotherapy cCRT: Concurrent Chemoradiotherapy CTV: Clinical Target Volume ECOG: Eastern Cooperative Oncology Group (performance status) EGFR: Epidermal Growth Factor Receptor EORTC: European Organisation for Research and Treatment of Cancer fSRT: Fractionated Stereotactic Radiotherapy GBM: Glioblastoma (WHO grade IV) GTV: Gross Tumor Volume Gy: Gray (unit of absorbed radiation dose) HF-RT: Hypofractionated Radiotherapy HR: Hazard Ratio IAEA: International Atomic Energy Agency IDH: Isocitrate Dehydrogenase IMRT: Intensity-Modulated Radiotherapy IQR: Interquartile Range KPS: Karnofsky Performance Status KM : Kaplan–Meier MGMT: O^6-Methylguanine-DNA Methyltransferase (promoter methylation) MRI: Magnetic Resonance Imaging OS : Overall Survival OAR: Organ at Risk PET: Positron Emission Tomography PH: Proportional Hazards (assumption) PTV: Planning Target Volume PFS: Progression-Free Survival RANO : Response Assessment in Neuro-Oncology RTOG: Radiation Therapy Oncology Group RT: Radiotherapy SD: Standard Deviation SRS: Stereotactic Radiosurgery SRT: Stereotactic Radiotherapy STR: Subtotal Resection TMZ: Temozolomide TTFields: Tumor Treating Fields VMAT: Volumetric Modulated Arc Therapy VEGF: Vascular Endothelial Growth Factor WHO: World Health Organization Declarations Conflict of interest The authors have declared no conflicts of interest. Ethics approval and consent to participate: All methods were carried out in accordance with relevant guidelines and regulations. The study received a positive vote and was approved by the Ethics Committee of the Medical Faculty of Martin Luther University Halle-Wittenberg (approval number: 2024-002). Owing to the retrospective nature of the study, the requirement for informed consent was waived by the Ethics Committee. Funding: No funding was received for this study. Clinical trial number: not applicable. All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ian Schirrwagen, Clara Pitzschel, Jörg Andreas Müller and Daniel Medenwald. The first draft of the manuscript was written by Jörg Andreas Müller and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ian Schirrwagen, Clara Pitzschel, Jörg Andreas Müller and Daniel Medenwald. The first draft of the manuscript was written by Jörg Andreas Müller and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgments None. Data Availability The data that support the findings of this study are derived from institutional cancer registry records and are not publicly available due to privacy and data protection regulations. Access to the data is restricted under German data protection law and the conditions of the ethics approval. Aggregated or anonymized data may be made available from the corresponding author upon reasonable request and with appropriate institutional permissions. References Schaff LR, Mellinghoff IK. Glioblastoma and Other Primary Brain Malignancies in Adults: A Review. JAMA. 2023; 329:574–87. doi: 10.1001/jama.2023.0023 PMID: 36809318. 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00:38:57","extension":"html","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":143174,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/561f47f122d4ece1bebac8ed.html"},{"id":97898599,"identity":"e2e4b6ef-6057-41ac-a313-de10c9588e05","added_by":"auto","created_at":"2025-12-10 15:39:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82494,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curve illustrating overall survival (OS) of the entire GBM cohort. Shaded area represents the 95% confidence interval.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/4dd3f56862a07e51ff759527.png"},{"id":97898320,"identity":"25319b7a-a7eb-48dc-a6af-912f92036b9e","added_by":"auto","created_at":"2025-12-10 15:39:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81528,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curve illustrating PFS of the entire GBM cohort. Shaded area represents the 95% confidence interval.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/782bf773673dc474de434e0a.png"},{"id":97832693,"identity":"5b181ca3-af87-4a39-b811-d3c904752b05","added_by":"auto","created_at":"2025-12-10 00:38:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":75526,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves for overall survival (OS) stratified by age (\u0026lt;70 vs. ≥70 years) in patients with GBM.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/ec627917834cdc29c011b65a.png"},{"id":97899225,"identity":"26155210-50b8-4867-a555-4bfaa05d1b0b","added_by":"auto","created_at":"2025-12-10 15:42:14","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":186738,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves for overall survival (OS) stratified by temozolomide treatment (yes vs. no) in patients with GBM.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/5cb30140b1251fbecc8a9780.jpeg"},{"id":98421007,"identity":"d8f5b122-5ec1-4527-b048-ce77d9805782","added_by":"auto","created_at":"2025-12-17 16:22:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1191913,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/f84e2f6f-9cd8-450f-9b28-00a3f3d787c2.pdf"},{"id":97832698,"identity":"bc5f3e1f-6e75-4a9a-9b55-0686b259b432","added_by":"auto","created_at":"2025-12-10 00:38:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":487504,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-8011713/v1/55cd7fadba39ad3dc0618e6f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Real-World Evidence on the Management and Outcomes of Glioblastoma in Elderly Patients: A Monocentric Retrospective Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalignant primary brain tumors, though relatively rare with an annual incidence of approximately 7 per 100,000 individuals, remain among the most devastating cancers, causing more than 15,000 deaths per year in the United States [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Glioblastoma (GBM) (WHO grade IV) represents nearly half of all malignant brain tumors and carries a particularly poor prognosis, with a five-year survival rate of only about 6\u0026ndash;7% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGBMs are traditionally divided into primary and secondary forms. Primary GBMs arise de novo, typically in older patients, whereas secondary GBMs develop from lower-grade diffuse astrocytomas and more often occur in younger individuals. Although histologically indistinguishable, these entities differ in their molecular profiles and clinical outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe growing importance of molecular diagnostics is also reflected in the 2021 WHO Classification of Central Nervous System Tumors, which emphasizes integrated histological and molecular diagnoses [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These developments highlight the heterogeneity of GBM. In addition to histopathological features, molecular markers such as IDH mutation status, TERT promoter mutations, and 1p/19q codeletion have emerged as critical classifiers. On the basis of these alterations, gliomas can be stratified into distinct molecular groups that differ in age at onset, clinical behavior, survival, and underlying genetic susceptibility, underscoring their distinct mechanisms of pathogenesis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Epigenetic alterations also play a crucial role in GBM biology and treatment response. In particular, methylation of the MGMT promoter has been shown to predict benefit from alkylating agents such as temozolomide (TMZ) and is an independent favorable prognostic factor [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe current standard of care consists of maximal safe surgical resection followed by combined radiotherapy (RT) and TMZ, which significantly improves survival compared with RT alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additional treatment modalities have been investigated to further improve outcomes. Tumor Treating Fields (TTFields), a non-invasive antimitotic therapy, demonstrated a significant prolongation of both progression-free and overall survival when added to maintenance TMZ in patients with newly diagnosed GBM, with a manageable toxicity profile primarily consisting of mild skin reactions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The vascular endothelial growth factor (VEGF) inhibitor bevacizumab, although widely used in recurrent disease, has not been shown to improve overall survival (OS) on a population level, despite potential benefits such as reduced corticosteroid dependence [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Retrospective and registry-based studies confirm the benefit of the Stupp protocol, with OS and PFS compared with pre-2004 cohorts, and have highlighted the potential role of second-line chemotherapy and radiosurgery at recurrence [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn elderly patients, therapeutic strategies require further adaptation due to limited tolerance to intensive treatment. Randomized trials have demonstrated that RT provides a modest survival benefit compared with supportive care alone, without impairing quality of life [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, hypofractionated RT regimens are non-inferior to conventional RT and offer advantages such as reduced treatment duration and lower corticosteroid requirements [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The addition of TMZ to short-course RT significantly prolongs survival, particularly in patients with MGMT promoter methylation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Similarly, randomized evidence supports both TMZ monotherapy and hypofractionated RT as reasonable treatment options in patients over 70 years, with MGMT methylation status serving as a predictive biomarker for treatment benefit [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile randomized clinical trials have defined the current standard of care for GBM, their strict eligibility criteria often exclude elderly patients, individuals with comorbidities, or those with poor performance status. Consequently, outcomes reported in these studies may not fully reflect the reality of daily clinical practice. In contrast, real-world data provide valuable insights into treatment patterns, prognostic factors, and survival outcomes across unselected and heterogeneous patient populations. Against this background, the aim of the present study is to analyze real-world outcomes of GBM patients treated at our institution in a monocentric, retrospective cohort, thereby complementing clinical trial evidence and contributing to a more comprehensive understanding of GBM care in routine practice.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData and material\u003c/h2\u003e\u003cp\u003ePatient recruitment was conducted retrospectively using the digital archives of the Department of Radiation Oncology at University Hospital Halle (Saale). Data were anonymized and extracted from the hospital information system ORBIS (version 03.20.02.01). Imaging diagnostics and RT data were obtained from Centricity PACS (GE Healthcare) and Elekta Mosaiq (version 2.84). All patients with histologically confirmed GBM (WHO grade IV) who received treatment between 2014 and 2023 were considered. The date of tumor progression was either obtained from the interdisciplinary tumor board documentation or derived from follow-up MRI imaging.\u003c/p\u003e\u003cp\u003e The study received a positive vote and was approved by the ethics committee of the Medical Faculty of Martin Luther University Halle-Wittenberg (2024-002).\u003c/p\u003e\u003cp\u003eClinical variables were categorized for statistical analysis. Age at diagnosis was recorded as a continuous variable (mean and range). Elderly status was defined as an age of \u0026ge;\u0026thinsp;65 years at the time of diagnosis. Sex was classified as male or female. Performance status was assessed using the Karnofsky Performance Status (KPS, reported as median and range) and, where available, the ECOG performance status.\u003c/p\u003e\u003cp\u003eMolecular profiles included MGMT promoter methylation status, IDH mutation status, TERT mutation, and EGFR amplification/mutation.\u003c/p\u003e\u003cp\u003eThe extent of resection was classified according to the EOR classification as gross total resection, near total resection, subtotal resection, or biopsy. Postoperative MRI within 48\u0026ndash;72 hours after surgery was evaluated for the presence of residual tumor (reported as percentage of patients with radiological evidence of tumor remnant). Primarily radiologic evaluation was used for the evaluation of tumor residual status.\u003c/p\u003e\u003cp\u003eRT parameters included fractionation scheme (normofractionated, hypofractionated, ultrahypofractionated), total dose (median, mean, range), dose per fraction, and overall treatment time. RT was considered complete if the full prescribed course was delivered.\u003c/p\u003e\u003cp\u003eChemotherapy with TMZ was recorded as a binary variable (yes/no) and further specified as concomitant and/or sequential administration. Additional variables included applied dose and the number of treatment cycles.\u003c/p\u003e\u003cp\u003eDexamethasone use was documented at treatment initiation and at the end of therapy (dosage in mg).\u003c/p\u003e\u003cp\u003eTumor site was classified by anatomical location (frontal, temporal, parietal, occipital, cerebellar, corpus callosum, brainstem, pons, deep white matter) and reported as percentage distribution. Tumor volumes were assessed as gross tumor volume (GTV and GTV recurrence) and clinical target volume (CTV and CTV recurrence), reported as mean, median, and standard deviation in cm\u0026sup3;.\u003c/p\u003e\u003cp\u003eProgression was categorized as in-field or out-of-field recurrence and summarized as percentage distribution.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eThe primary endpoint of this study was overall survival (OS), while progression-free survival (PFS) was defined as the secondary endpoint. PFS and OS were calculated from the end of RT. PFS was defined as the time from the last day of radiotherapy to the date of radiologically or clinically confirmed tumor progression or death from any cause, whichever occurred first. OS was defined as the time from the last day of radiotherapy to death from any cause. Patients without an event were censored at the date of last follow-up. To evaluate the association between clinical and treatment-related parameters and survival outcomes, Cox proportional hazards regression models were applied.\u003c/p\u003e\u003cp\u003eIn a first step, univariable Cox regression analyses were performed including the following covariates: age, sex, performance status (Karnofsky Performance Status [KPS], extent of resection (total resection vs. other) and the administration of TMZ (yes vs. no). Gross tumor volume (GTV) and molecular markers were explored in preliminary models but were not retained for final analysis due to limited data availability and lack of statistical significance.\u003c/p\u003e\u003cp\u003eAll variables that reached statistical significance in the univariable analyses were subsequently included in the multivariable Cox regression model. The results were expressed as hazard ratios (HR) with 95% confidence intervals (CI), and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003eTo ensure the robustness of the findings, sensitivity analyses were performed. These included adjustment for the updated WHO 2021 glioma classification, as well as stratified analyses according to the main clinical predictors (age, sex, KPS, extent of resection, and TMZ use). Model diagnostics were performed by plotting Schoenfeld residuals to evaluate model fit and formally testing the proportional hazards assumption.\u003c/p\u003e\u003cp\u003eKaplan\u0026ndash;Meier survival curves were generated to illustrate OS and PFS in the entire cohort and to visualize differences between clinically relevant subgroups. Stratified analyses were presented according to age (\u0026lt;\u0026thinsp;70 vs. \u0026ge;70 years), sex, KPS (\u0026lt;\u0026thinsp;70% vs. \u0026ge;70%), extent of resection (total resection vs. other), and TMZ treatment (yes vs. no).\u003c/p\u003e\u003cp\u003eAll statistical analyses were conducted using RStudio, version 2024.04.2\u0026thinsp;+\u0026thinsp;764. During the preparation of this work, the authors used ChatGPT, a language model developed by OpenAI Inc., to improve writing style and check grammar and spelling. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the final manuscript.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003ePatient characteristics\u003c/h2\u003e\n\u003cp\u003eA total of n=67 patients with histologically confirmed glioblastoma (GBM) were included in the analysis (Table 1). The median age at diagnosis was 73.7 years (range 65\u0026ndash;88 years). Thirty-seven patients (55%) were male and 30 patients (45%) were female. The median Karnofsky Performance Status (KPS) at baseline was 60% (range 30\u0026ndash;100%), with data missing for five patients.\u003c/p\u003e\n\u003cp\u003eWith respect to molecular markers, MGMT promoter status was methylated in 36 patients (54%), unmethylated in 24 patients (36%), and unknown in 7 patients (10%). IDH mutation was not observed; 56 patients (84%) had wild-type status, and 11 patients (16%) had unknown status.\u003c/p\u003e\n\u003cp\u003eRegarding surgical treatment, 28 patients (42%) underwent gross total resection, 17 patients (25%) near-total resection, 2 patients (3%) subtotal resection, and 16 patients (24%) biopsy, while 4 patients (6%) had missing information on resection status.\u003c/p\u003e\n\u003cp\u003eRT was delivered as normofractionated treatment in 15 patients (22%), hypofractionated in 43 patients (64%), and ultrahypofractionated in 9 patients (13%). The median total dose was 40 Gy (range 5\u0026ndash;60 Gy). Concomitant or sequential chemotherapy with temozolomide (TMZ) was administered in 42 patients (63%), while 25 patients (37%) did not receive TMZ.\u003c/p\u003e\n\u003cp\u003eVolumetric data were available for most patients. The mean gross tumor volume (GTV) was 205 cm\u0026sup3; (median 40 cm\u0026sup3;, maximum 1,201 cm\u0026sup3;; missing in 7 patients), and the mean clinical target volume (CTV) was 149 cm\u0026sup3; (median 142 cm\u0026sup3;, Q1 = 75; missing in 24 patients).\u003c/p\u003e\n\u003cp\u003ePatterns of recurrence could be classified in 17 patients (25%), with 3 in-field (4.6%) and 14 out-of-field (22%) recurrences, while the majority (n = 50; 75%) had missing or indeterminate data.\u003c/p\u003e\n\u003cp\u003eRadiologic evidence of residual tumor after surgery was reported in 37 patients (55%), absent in 18 patients (27%), and unknown in 12 patients (18%).\u003c/p\u003e\n\u003cp\u003eTreatment with tumor treating fields (TTF) was initiated in 6 patients (9%), whereas 55 patients (82%) did not receive TTF therapy. In an additional 6 patients (9%), information on TTF use was missing.\u003c/p\u003e\n\u003cp\u003eA complete overview of all patient characteristics, including detailed comorbidities and supportive treatment data, is provided in \u003cstrong\u003eTable S1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eWhen comparing baseline characteristics between male and female patients, no statistically significant age difference was observed (median 73.0 vs. 74.0 years, p = 0.082). However, women presented with a significantly lower median Karnofsky Performance Status (KPS) compared to men (60% vs. 70%, p = 0.021).\u003c/p\u003e\n\u003cp\u003eWith respect to molecular markers, MGMT promoter methylation differed significantly between sexes (p = 0.019). A higher proportion of female patients had methylated MGMT promoter status (67% vs. 43%), while unmethylated status was more frequent among men (38% vs. 33%), and MGMT status was unknown in 19% of male but in none of the female patients.\u003c/p\u003e\n\u003cp\u003eNo significant differences were found between men and women regarding radiotherapy regimen (p = 0.6) or surgical resection status (p = 0.2). The distribution of radiotherapy schemes was comparable, with hypofractionated regimens being most common in both groups (59% in men vs. 70% in women). A trend toward more frequent omission of temozolomide (TMZ) in female patients was observed (50% vs. 27% in men, p = 0.076).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Baseline clinical, molecular, and treatment characteristics of patients with GBM.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"504\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eN = 67\u003c/strong\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73.7 (65.0, 88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKarnofsky-Index [%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60 (30, 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMGMT-status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; unmethylated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; methylated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eIDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; wild-type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56 (84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; unkown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResection status (EOR classification)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Gross total resection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Near total resection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Subtotal resection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Biospy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRadiotherapy - scheme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; normofractionated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; hypofractionated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; ultrahypofrationated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTotal Dose [Gy]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40 (5, 60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTemozolomide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42 (63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGTV [cm\u0026sup3;]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e205, 40, 1,201\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCTV [cm\u0026sup3;]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e149, 142, 75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRecurrence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; In-field\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Out-field\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRadiology showing rest of malignoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; unknwon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTTF-treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55 (82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e Mean (Min, Max); n (%); Median (Min, Max); Median (Q1, Q3); Mean, Median, SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eSurvival analyses\u003c/h2\u003e\n\u003cp\u003eIn the entire cohort of 71 patients, the median OS was 7.0 months (interquartile range [IQR] 5.5\u0026ndash;13.0 months), with 25% of patients surviving less than 3.2 months and 25% surviving longer than 23 months. When stratified by MGMT promoter methylation status, patients with methylated tumors had a median OS of 8.1 months (IQR 5.3\u0026ndash;21.0 months), with the 25th and 75th percentiles at 4.9 and 24.0 months, respectively. In contrast, patients with unmethylated tumors showed a median OS of 8.8 months (IQR 5.5\u0026ndash;23.0 months), with the 25th and 75th percentiles at 3.6 and 23.0 months, respectively. Among male patients, overall survival (OS) at six months was highest in the normofractionated group (73.3%), followed by hypofractionated RT (58.1%) and ultrahypofractionated RT (22.2%). At twelve months, OS rates declined to 60.0%, 37.2%, and 0.0%, respectively. Progression-free survival (PFS) showed a similar trend, with six-month PFS of 53.3% (normofractionated), 43.4% (hypofractionated), and 11.1% (ultrahypofractionated), and corresponding twelve-month rates of 40.0%, 26.5%, and 0.0%.\u0026nbsp;Among\u0026nbsp;female patients, survival outcomes were overall lower compared to men. Six-month OS rates were 60.0% for normofractionated, 50.0% for hypofractionated, and 25.0% for ultrahypofractionated RT, while twelve-month OS rates were 40.0%, 28.6%, and 0.0%, respectively. For PFS, six-month rates were 65.0%, 55.0%, and 33.0%, declining to 50.0%, 30.0%, and 0.0% at twelve months.\u003c/p\u003e\n\u003cp\u003eIn univariable Cox regression analyses, increasing age was significantly associated with worse OS (HR 1.08, 95% CI 1.02\u0026ndash;1.13, p = 0.004). Female sex was not significantly associated with OS in the univariable model (HR 0.83, 95% CI 0.50\u0026ndash;1.37, p = 0.50). A higher KPS was significantly associated with better prognosis (HR 0.98, 95% CI 0.96\u0026ndash;0.99, p = 0.006). Omission of TMZ was strongly associated with inferior survival (HR 2.65, 95% CI 1.53\u0026ndash;4.59, p \u0026lt; 0.001). Regarding resection status, total resection showed a trend toward improved OS compared to other resection types (HR 0.59, 95% CI 0.33\u0026ndash;1.07, p = 0.074).\u003c/p\u003e\n\u003cp\u003eIn the multivariable Cox regression model, age remained independently associated with worse OS (HR 1.07, 95% CI 1.00\u0026ndash;1.14, p = 0.043). Female sex emerged as an independent prognostic factor for improved survival (HR 0.50, 95% CI 0.26\u0026ndash;0.98, p = 0.044). Omission of TMZ remained a strong predictor of inferior survival (HR 2.41, 95% CI 1.24\u0026ndash;4.66, p = 0.009). Total resection was independently associated with improved OS (HR 0.50, 95% CI 0.26\u0026ndash;0.96, p = 0.037). A higher KPS also showed a trend toward improved OS (HR 0.98, 95% CI 0.96\u0026ndash;1.00, p = 0.064).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;A detailed summary of the univariable and multivariable Cox regression analyses is provided in Table 2, and Kaplan\u0026ndash;Meier curves for OS according to relevant clinical subgroups are shown in Figures 1\u0026ndash;4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Results of univariable and multivariable Cox regression analyses for OS in patients with GBM. Shown are HR with corresponding 95% CI.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"431\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02, 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00, 1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50, 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.26, 0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTemozolomide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.53, 4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.24, 4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResection status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Rest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.33, 1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.26, 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKarnofsky\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96, 0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96, 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eAbbreviations: CI = Confidence Interval, HR = Hazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe median PFS was 5.0 months (IQR 3.6\u0026ndash;7.9 months), with 25% of patients progressing within 2.3 months and 25% remaining progression-free for more than 13 months. When stratified by MGMT promoter methylation status, patients with methylated tumors had a median PFS of 5.3 months (IQR 3.6\u0026ndash;14.0 months), with the 25th and 75th percentiles at 2.6 and 17.0 months, respectively. Patients with unmethylated tumors had a median PFS of 5.6 months (IQR 3.2\u0026ndash;10.0 months), with the 25th and 75th percentiles at 2.8 and 10.0 months, respectively.\u003c/p\u003e\n\u003cp\u003eIn univariable Cox regression analyses, age was significantly associated with shorter PFS (HR 1.06, 95% CI 1.01\u0026ndash;1.11, p = 0.019). Female sex was not significantly associated with PFS (HR 0.72, 95% CI 0.43\u0026ndash;1.20, p = 0.20). Omission of temozolomide (TMZ) was significantly associated with worse PFS (HR 2.40, 95% CI 1.37\u0026ndash;4.20, p = 0.003). Total resection showed a non-significant trend toward better PFS compared to non-total resection (HR 0.62, 95% CI 0.34\u0026ndash;1.12, p = 0.10). A higher Karnofsky Performance Status (KPS) was significantly associated with improved PFS (HR 0.97, 95% CI 0.96\u0026ndash;0.99, p = 0.004).\u003c/p\u003e\n\u003cp\u003eIn the multivariable Cox regression model, age remained significantly associated with shorter PFS (HR 1.06, 95% CI 1.00\u0026ndash;1.13, p = 0.038). Female sex was independently associated with better PFS (HR 0.41, 95% CI 0.21\u0026ndash;0.80, p = 0.009). Lack of TMZ treatment continued to be significantly associated with inferior PFS (HR 2.31, 95% CI 1.20\u0026ndash;4.46, p = 0.013). Total resection again was not significantly associated with PFS (HR 0.62, 95% CI 0.33\u0026ndash;1.17, p = 0.14). Higher KPS remained significantly associated with improved PFS (HR 0.98, 95% CI 0.95\u0026ndash;1.00, p = 0.024).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;A detailed summary of the univariable and multivariable Cox regression analyses for PFS is presented in \u003cstrong\u003eTable 3\u003c/strong\u003e. Supplementary Kaplan\u0026ndash;Meier curves for PFS according to relevant clinical subgroups are provided in Figures 3 and S1\u0026ndash;S4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Results of univariable and multivariable Cox regression analyses for PFS in patients with GBM. Shown are HR with corresponding 95% CI and p-values.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.01, 1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00, 1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.43, 1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21, 0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTemozolomide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.37, 4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.20, 4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResection status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; non-total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.34, 1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.33, 1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKarnofsky Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96, 0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.95, 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003eAbbreviations: CI = Confidence Interval, HR = Hazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity Analyses\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;In sensitivity analyses, the results of the multivariable models for OS and PFS remained largely consistent. Tests of the proportional hazards assumption did not indicate relevant deviations for OS (global p = 0.164) or PFS (global p = 0.086). For OS, all covariates showed stable hazard ratios over time (age p = 0.999, sex p = 0.755, KPS p = 0.160, TMZ p = 0.424, resection status p = 0.058). For PFS, a deviation from the proportional hazards assumption was observed for resection status (p = 0.010), while all other variables fulfilled the assumption (age p = 0.634, sex p = 0.792, KPS p = 0.381, TMZ p = 0.131).\u003c/p\u003e\n\u003cp\u003eInspection of Schoenfeld residual plots suggested only mild time-dependent effects for resection status in the PFS model, with no substantial violations for the remaining covariates. The corresponding Schoenfeld residual plots for the main prognostic covariates are shown in Figure S5. Given these findings, no model stratification was deemed necessary, and the main prognostic associations for both OS and PFS were considered robust. The detailed numerical results of these tests, including chi-square statistics and p-values for individual covariates as well as the global model, are summarized in \u003cstrong\u003eTable S2\u003c/strong\u003e (\u003cem\u003eTests of the proportional hazards assumption for OS and PFS in patients with glioblastoma\u003c/em\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this monocentric, retrospective real-world analysis of elderly and predominantly frail patients with histologically confirmed GBM, we observed a median overall survival (OS) of 7.0 months and a median progression-free survival (PFS) of 5.0 months. Multivariable analyses identified younger age, higher performance status, total resection, and concomitant temozolomide (TMZ) as independent predictors of improved outcomes. Sensitivity and subgroup analyses confirmed the robustness of these findings, underscoring the prognostic value of established clinical and treatment-related parameters in this vulnerable patient population.\u003c/p\u003e\u003cp\u003eOur results align with prior randomized and prospective evidence evaluating radiotherapy (RT) fractionation and chemotherapy in elderly GBM. The majority of patients (63%) received hypofractionated RT, reflecting a preference for shorter treatment courses in older populations (median age 73.6 years, median KPS 60%). The median OS of 7.0 months corresponds closely to findings by Roa et al., who reported comparable survival for 40 Gy in 15 fractions versus conventional 60 Gy schedules in patients aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years, with reduced treatment burden and steroid use in the shorter regimen [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Similarly, Jablonska et al. prospectively investigated hypofractionated RT with concomitant TMZ in elderly patients with poor prognostic features, reporting a median OS and PFS of 7 months[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], consistent with our observations.\u003c/p\u003e\u003cp\u003eThe randomized phase III IAEA trial by Roa, Kepka et al. compared an ultra-short RT regimen (25 Gy in 5 fractions) with the standard 40 Gy in 15 fractions in elderly and frail GBM patients. Non-inferiority of the 1-week schedule was demonstrated, with median OS 7.9 vs. 6.4 months and comparable PFS (4.2 months in both arms), alongside preserved quality of life and reduced treatment burden [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our cohort, 13% received ultrahypofractionated RT, reflecting the clinical adoption of this approach. The median OS of 7.0 months observed here\u0026mdash;predominantly under hypofractionated or ultrahypofractionated schedules\u0026mdash;is consistent with the IAEA data and supports condensed RT as a feasible option for elderly or frail GBM patients.\u003c/p\u003e\u003cp\u003eThe Nordic trial by Malmstr\u0026ouml;m et al. also demonstrated that both hypofractionated RT and TMZ monotherapy achieved superior survival compared with conventional RT in patients\u0026thinsp;\u0026gt;\u0026thinsp;70 years (median OS 7.5 and 8.3 months vs. 6.0 months) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although our cohort was too small for statistical comparison of fractionation schemes, outcomes were comparable to those trials, reinforcing hypofractionation as a practical standard.\u003c/p\u003e\u003cp\u003eMore recently, Zemskova et al. retrospectively compared conventional and hypofractionated RT and found better outcomes with conventional schedules in patients with good KPS and limited disease [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our findings differ, likely reflecting the older and frailer nature of our population, where hypofractionation was predominant and yielded survival comparable to prospective studies. Taken together, our results confirm the clinical suitability of hypofractionated RT, particularly when combined with TMZ and adequate resection, in elderly GBM patients.\u003c/p\u003e\u003cp\u003eIncreasing age was independently associated with worse OS and PFS, consistent with prior studies demonstrating that both chronological and biological age negatively affect survival [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The relatively narrow age range in our series (65\u0026ndash;88 years) may have limited discrimination across subgroups, but the continuous association between age and prognosis persisted, emphasizing age as a relevant prognostic dimension even within older populations.\u003c/p\u003e\u003cp\u003eOther studies have reported more nuanced results. Hallaert et al. did not confirm an independent prognostic effect of sex after adjustment for MGMT, age, and extent of resection but validated MGMT methylation as a key biomarker [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In our data, patients with unmethylated MGMT promoter status showed slightly longer median OS (8.8 vs. 8.1 months) and PFS (5.6 vs. 5.3 months) than those with methylated tumors, although these differences were not statistically significant. This inversion compared with prior literature likely reflects small subgroup sizes and incomplete molecular data. Overall, the influence of MGMT status was outweighed by clinical and treatment-related factors such as resection and TMZ use.\u003c/p\u003e\u003cp\u003eIncreasing age was independently associated with worse OS and PFS, consistent with prior studies demonstrating that both chronological and biological age negatively affect survival [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The relatively narrow age range in our series (65\u0026ndash;88 years) may have limited discrimination across subgroups, but the continuous association between age and prognosis persisted, emphasizing age as a relevant prognostic dimension even within older populations.\u003c/p\u003e\u003cp\u003eRecurrence classification was available for 24% of patients, with 4.6% showing in-field and 22% out-of-field progression. While most published series report predominantly local or in-field recurrences, our higher proportion of out-of-field failures likely reflects selection bias, limited follow-up imaging, and small numbers of evaluable events. Murakami et al. and Tu et al. emphasized that local control is largely determined by resection extent and GTV margin definition [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while Zheng et al. showed that omitting peritumoral FLAIR abnormalities can safely reduce irradiated volume [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In line with these findings, our data suggest that local tumor control and individualized target delineation remain central to optimizing outcomes. Future work should further investigate tumor volume as a prognostic factor in elderly real-world cohorts.\u003c/p\u003e\u003cp\u003eMurakami et al. emphasized that control of the macroscopic tumor bulk determines the length of the progression-free interval [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Contemporary reirradiation studies also underline the relevance of tumor volume and margin selection: Margulies et al. reported higher rates of marginal and out-of-field failures with smaller GTV-to-PTV margins (1 mm) and larger PTV volumes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], while adaptive strategies have been shown to optimize tumor coverage and reduce normal tissue dose in the presence of tumor shrinkage or expansion [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Together, these data support precise, GTV-focused contouring with carefully balanced margins (as suggested by Tu and Zheng) and consideration of adaptive replanning when volumetric changes occur. Future studies should also focus on tumor volume as prognostic factor in terms of real-world outcomes.\u003c/p\u003e\u003cp\u003eConcomitant TMZ remained a strong independent predictor of improved OS and PFS, consistent with the survival benefit demonstrated in the Stupp trial [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and subsequent real-world analyses [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Patients who did not receive TMZ were older (median 76 years) and had lower KPS (median 55%), suggesting that treatment omission was largely due to frailty and comorbidity. These patients often had IDH-wildtype, MGMT-unmethylated tumors and underwent limited surgery, indicating an unfavorable biological and clinical profile. Most were treated with hypofractionated or ultrahypofractionated RT, consistent with palliative intent and reduced treatment tolerance.\u003c/p\u003e\u003cp\u003eOnly a small subset (n\u0026thinsp;=\u0026thinsp;6, 9%) received tumor treating fields (TTF), precluding meaningful statistical analysis. The limited use likely reflects the advanced age, frailty, and logistical barriers inherent to TTF therapy in this population.\u003c/p\u003e\u003cp\u003eLimitations and strengths\u003c/p\u003e\u003cp\u003eThis study\u0026rsquo;s retrospective, single-center design and modest sample size limit generalizability and increase the potential for bias. Missing molecular and volumetric data, as well as incomplete follow-up imaging, restricted detailed assessment of recurrence patterns. Nevertheless, the dataset represents unselected, real-world elderly GBM patients\u0026mdash;an underrepresented group in clinical trials. Most patients were treated according to guideline-based standards, with adherence to combined chemoradiation regimens when feasible.\u003c/p\u003e\u003cp\u003eStatistical robustness was supported by multivariable Cox regression and sensitivity testing using Schoenfeld residuals, which confirmed no relevant proportional hazards violations. The integration of demographic, surgical, and RT parameters provides a comprehensive perspective on prognostic factors in daily clinical practice.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this retrospective real-world cohort of elderly patients with GBM, overall and progression-free survival remained poor despite multimodal therapy. Increasing age was independently associated with worse outcomes, whereas female sex (for PFS), higher performance status, total resection, and concomitant TMZ treatment were linked to improved survival. The majority of patients received hypofractionated or ultrahypofractionated RT, with survival outcomes comparable to those reported in prospective trials. These findings reinforce the prognostic relevance of established clinical and treatment-related factors and support the use of condensed, evidence-based treatment schedules in the management of elderly and frail GBM patients.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eCI:\u003c/strong\u003e Confidence Interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRT:\u003c/strong\u003e Chemoradiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ecCRT:\u0026nbsp;\u003c/strong\u003eConcurrent Chemoradiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCTV:\u0026nbsp;\u003c/strong\u003eClinical Target Volume\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eECOG:\u003c/strong\u003e Eastern Cooperative Oncology Group (performance status)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEGFR:\u0026nbsp;\u003c/strong\u003eEpidermal Growth Factor Receptor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEORTC:\u003c/strong\u003e European Organisation for Research and Treatment of Cancer\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efSRT:\u0026nbsp;\u003c/strong\u003eFractionated Stereotactic Radiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGBM:\u0026nbsp;\u003c/strong\u003eGlioblastoma (WHO grade IV)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGTV:\u003c/strong\u003e Gross Tumor Volume\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGy:\u0026nbsp;\u003c/strong\u003eGray (unit of absorbed radiation dose)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHF-RT:\u0026nbsp;\u003c/strong\u003eHypofractionated Radiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHR:\u0026nbsp;\u003c/strong\u003eHazard Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;IAEA:\u003c/strong\u003e International Atomic Energy Agency\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIDH:\u0026nbsp;\u003c/strong\u003eIsocitrate Dehydrogenase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIMRT:\u0026nbsp;\u003c/strong\u003eIntensity-Modulated Radiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIQR:\u0026nbsp;\u003c/strong\u003eInterquartile Range\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKPS:\u0026nbsp;\u003c/strong\u003eKarnofsky Performance Status\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKM\u003c/strong\u003e: Kaplan\u0026ndash;Meier\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMGMT:\u0026nbsp;\u003c/strong\u003eO^6-Methylguanine-DNA Methyltransferase (promoter methylation)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMRI:\u003c/strong\u003e Magnetic Resonance Imaging\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOS\u003c/strong\u003e: Overall Survival\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOAR:\u0026nbsp;\u003c/strong\u003eOrgan at Risk\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePET:\u0026nbsp;\u003c/strong\u003ePositron Emission Tomography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePH:\u0026nbsp;\u003c/strong\u003eProportional Hazards (assumption)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePTV:\u0026nbsp;\u003c/strong\u003ePlanning Target Volume\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePFS:\u0026nbsp;\u003c/strong\u003eProgression-Free Survival\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRANO\u003c/strong\u003e: Response Assessment in Neuro-Oncology\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRTOG:\u0026nbsp;\u003c/strong\u003eRadiation Therapy Oncology Group\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRT:\u0026nbsp;\u003c/strong\u003eRadiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSD:\u0026nbsp;\u003c/strong\u003eStandard Deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSRS:\u0026nbsp;\u003c/strong\u003eStereotactic Radiosurgery\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSRT:\u0026nbsp;\u003c/strong\u003eStereotactic Radiotherapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSTR:\u0026nbsp;\u003c/strong\u003eSubtotal Resection\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTMZ:\u0026nbsp;\u003c/strong\u003eTemozolomide\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTTFields:\u0026nbsp;\u003c/strong\u003eTumor Treating Fields\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVMAT:\u0026nbsp;\u003c/strong\u003eVolumetric Modulated Arc Therapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVEGF:\u0026nbsp;\u003c/strong\u003eVascular Endothelial Growth Factor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWHO:\u0026nbsp;\u003c/strong\u003eWorld Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of interest\u003c/h2\u003e\n\u003cp\u003eThe authors have declared no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\n\u003cp\u003eAll methods were carried out in accordance with relevant guidelines and regulations. The study received a positive vote and was approved by the Ethics Committee of the Medical Faculty of Martin Luther University Halle-Wittenberg (approval number: 2024-002). Owing to the retrospective nature of the study, the requirement for informed consent was waived by the Ethics Committee.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ian Schirrwagen, Clara Pitzschel, J\u0026ouml;rg Andreas M\u0026uuml;ller and Daniel Medenwald. The first draft of the manuscript was written by J\u0026ouml;rg Andreas M\u0026uuml;ller and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ian Schirrwagen, Clara Pitzschel, J\u0026ouml;rg Andreas M\u0026uuml;ller and Daniel Medenwald. The first draft of the manuscript was written by J\u0026ouml;rg Andreas M\u0026uuml;ller and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are derived from institutional cancer registry records and are not publicly available due to privacy and data protection regulations. Access to the data is restricted under German data protection law and the conditions of the ethics approval. Aggregated or anonymized data may be made available from the corresponding author upon reasonable request and with appropriate institutional permissions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSchaff LR, Mellinghoff IK. Glioblastoma and Other Primary Brain Malignancies in Adults: A Review. JAMA. 2023; 329:574\u0026ndash;87. doi: 10.1001/jama.2023.0023 PMID: 36809318.\u003c/li\u003e\n \u003cli\u003eOhgaki H, Kleihues P. The definition of primary and secondary glioblastoma. Clin Cancer Res. 2013; 19:764\u0026ndash;72. Epub 2012/12/03. doi: 10.1158/1078-0432.CCR-12-3002 PMID: 23209033.\u003c/li\u003e\n \u003cli\u003eLouis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. 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Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005; 352:987\u0026ndash;96. doi: 10.1056/NEJMoa043330 PMID: 15758009.\u003c/li\u003e\n \u003cli\u003eStupp R, Taillibert S, Kanner A, Read W, Steinberg D, Lhermitte B, et al. Effect of Tumor-Treating Fields Plus Maintenance Temozolomide vs Maintenance Temozolomide Alone on Survival in Patients With Glioblastoma: A Randomized Clinical Trial. JAMA. 2017; 318:2306\u0026ndash;16. doi: 10.1001/jama.2017.18718 PMID: 29260225.\u003c/li\u003e\n \u003cli\u003eGramatzki D, Roth P, Rushing EJ, Weller J, Andratschke N, Hofer S, et al. Bevacizumab may improve quality of life, but not overall survival in glioblastoma: an epidemiological study. Ann Oncol. 2018; 29:1431\u0026ndash;6. doi: 10.1093/annonc/mdy106 PMID: 29617713.\u003c/li\u003e\n \u003cli\u003eNava F, Tramacere I, Fittipaldo A, Bruzzone MG, Dimeco F, Fariselli L, et al. Survival effect of first- and second-line treatments for patients with primary glioblastoma: a cohort study from a prospective registry, 1997-2010. Neuro Oncol. 2014; 16:719\u0026ndash;27. Epub 2014/01/23. doi: 10.1093/neuonc/not316 PMID: 24463354.\u003c/li\u003e\n \u003cli\u003eKeime-Guibert F, Chinot O, Taillandier L, Cartalat-Carel S, Frenay M, Kantor G, et al. Radiotherapy for glioblastoma in the elderly. N Engl J Med. 2007; 356:1527\u0026ndash;35. doi: 10.1056/NEJMoa065901 PMID: 17429084.\u003c/li\u003e\n \u003cli\u003eRoa W, Brasher PMA, Bauman G, Anthes M, Bruera E, Chan A, et al. Abbreviated course of radiation therapy in older patients with glioblastoma multiforme: a prospective randomized clinical trial. J Clin Oncol. 2004; 22:1583\u0026ndash;8. Epub 2004/03/29. doi: 10.1200/JCO.2004.06.082 PMID: 15051755.\u003c/li\u003e\n \u003cli\u003ePerry JR, Laperriere N, O\u0026apos;Callaghan CJ, Brandes AA, Menten J, Phillips C, et al. Short-Course Radiation plus Temozolomide in Elderly Patients with Glioblastoma. N Engl J Med. 2017; 376:1027\u0026ndash;37. doi: 10.1056/NEJMoa1611977 PMID: 28296618.\u003c/li\u003e\n \u003cli\u003eMalmstr\u0026ouml;m A, Gr\u0026oslash;nberg BH, Marosi C, Stupp R, Frappaz D, Schultz H, et al. Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: the Nordic randomised, phase 3 trial. Lancet Oncol. 2012; 13:916\u0026ndash;26. Epub 2012/08/08. doi: 10.1016/S1470-2045(12)70265-6 PMID: 22877848.\u003c/li\u003e\n \u003cli\u003eJablonska PA, Diez-Valle R, P\u0026eacute;rez-Larraya JG, Moreno-Jim\u0026eacute;nez M, Idoate M\u0026Aacute;, Arbea L, et al. Hypofractionated radiation therapy and temozolomide in patients with glioblastoma and poor prognostic factors. A prospective, single-institution experience. PLoS One. 2019; 14:e0217881. Epub 2019/06/06. doi: 10.1371/journal.pone.0217881 PMID: 31170245.\u003c/li\u003e\n \u003cli\u003eRoa W, Kepka L, Kumar N, Sinaika V, Matiello J, Lomidze D, et al. International Atomic Energy Agency Randomized Phase III Study of Radiation Therapy in Elderly and/or Frail Patients With Newly Diagnosed Glioblastoma Multiforme. J Clin Oncol. 2015; 33:4145\u0026ndash;50. Epub 2015/09/21. doi: 10.1200/JCO.2015.62.6606 PMID: 26392096.\u003c/li\u003e\n \u003cli\u003eZemskova O, Pedachenko E, Yu NY, Rades D. Hypo-fractionated Radiotherapy (HF-RT) Versus Conventionally Fractionated Radiotherapy (CF-RT) for Glioblastoma. Anticancer Res. 2023; 43:3121\u0026ndash;8. doi: 10.21873/anticanres.16484 PMID: 37351960.\u003c/li\u003e\n \u003cli\u003eReihanian Z, Abbaspour E, Zaresharifi N, Karimzadhagh S, Mahmoudalinejad M, Sourati A, et al. Impact of Age and Gender on Survival of Glioblastoma Multiforme Patients: A Multicenter Retrospective Study. Cancer Rep (Hoboken). 2024; 7:e70050. doi: 10.1002/cnr2.70050 PMID: 39506810.\u003c/li\u003e\n \u003cli\u003eHallaert G, Pinson H, van den Broecke C, van Roost D, Kalala JP, Boterberg T. Sex-based survival differences in IDH-wildtype glioblastoma: Results from a retrospective cohort study. J Clin Neurosci. 2021; 91:209\u0026ndash;13. Epub 2021/07/16. doi: 10.1016/j.jocn.2021.07.008 PMID: 34373029.\u003c/li\u003e\n \u003cli\u003eMurakami R, Hirai T, Nakamura H, Furusawa M, Nakaguchi Y, Uetani H, et al. Recurrence patterns of glioblastoma treated with postoperative radiation therapy: relationship between extent of resection and progression-free interval. Jpn J Radiol. 2012; 30:193\u0026ndash;7. Epub 2011/12/20. doi: 10.1007/s11604-011-0031-x PMID: 22183828.\u003c/li\u003e\n \u003cli\u003eTu Z, Xiong H, Qiu Y, Li G, Wang L, Peng S. Limited recurrence distance of glioblastoma under modern radiotherapy era. BMC Cancer. 2021; 21:720. Epub 2021/06/22. doi: 10.1186/s12885-021-08467-3 PMID: 34154559.\u003c/li\u003e\n \u003cli\u003eZheng L, Zhou Z-R, Yu Q, Shi M, Yang Y, Zhou X, et al. The Definition and Delineation of the Target Area of Radiotherapy Based on the Recurrence Pattern of Glioblastoma After Temozolomide Chemoradiotherapy. Front Oncol. 2020; 10:615368. Epub 2021/02/22. doi: 10.3389/fonc.2020.615368 PMID: 33692942.\u003c/li\u003e\n \u003cli\u003eMargulies A, Sahki N, Rech F, Vogin G, Blonski M, Peiffert D, et al. Pattern of recurrence after fractionated stereotactic reirradiation in adult glioblastoma. Radiat Oncol. 2025; 20:28. Epub 2025/02/28. doi: 10.1186/s13014-025-02611-0 PMID: 40022217.\u003c/li\u003e\n \u003cli class=\"CitaviBibliographyEntry\"\u003e\u003cspan lang=\"EN-US\"\u003eŞenkesen \u0026Ouml;, Tezcanlı E, Abacıoğlu MU, \u0026Ouml;zen Z, \u0026Ccedil;\u0026ouml;ne D, K\u0026uuml;\u0026ccedil;\u0026uuml;c\u0026uuml;k H, et al. Limited field adaptive radiotherapy for glioblastoma: changes in target volume and organ at risk doses. Radiat Oncol J. 2022; 40:9\u0026ndash;19. Epub 2022/03/28. doi: 10.3857/roj.2021.00542 PMID: 35368196.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003evan Nguyen D, Nguyen NTT, Nguyen PH, Nguyen HT, Do TC. Evaluating treatment outcome of Glioblastoma with Stupp\u0026apos;s regimen: an experienced in single Institute. Chin Clin Oncol. 2025; 14:18. doi: 10.21037/cco-24-103 PMID: 40337874.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"glioblastoma, elderly, survival, temozolomide, chemoradiotherapy","lastPublishedDoi":"10.21203/rs.3.rs-8011713/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8011713/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eGlioblastoma (GBM) carries a poor prognosis, and elderly or frail patients are often underrepresented in randomized trials. This study evaluated real-world outcomes and prognostic factors in a monocentric cohort of elderly GBM patients.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eWe retrospectively analyzed 67 patients aged\u0026thinsp;\u0026ge;\u0026thinsp;65 years with histologically confirmed GBM treated between 2014 and 2023 at a single institution. Overall survival (OS) was defined as the primary endpoint, and progression-free survival (PFS) as the secondary endpoint. Univariable and multivariable Cox proportional hazards regression models were applied to assess prognostic factors, including age, sex, Karnofsky Performance Status (KPS), extent of resection, and temozolomide (TMZ) administration. Sensitivity analyses included proportional hazards testing using Schoenfeld residuals.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eThe median OS was 7.0 months (interquartile range [IQR] 5.5\u0026ndash;13.0), and the median PFS was 5.0 months (IQR 3.6\u0026ndash;7.9). In multivariable analyses, increasing age was independently associated with worse OS (HR 1.07, 95% CI 1.00\u0026ndash;1.14, p\u0026thinsp;=\u0026thinsp;0.043) and PFS (HR 1.06, 95% CI 1.00\u0026ndash;1.13, p\u0026thinsp;=\u0026thinsp;0.038). Female sex was independently associated with improved OS (HR 0.50, 95% CI 0.26\u0026ndash;0.98, p\u0026thinsp;=\u0026thinsp;0.044) and PFS (HR 0.41, 95% CI 0.21\u0026ndash;0.80, p\u0026thinsp;=\u0026thinsp;0.009). Higher KPS was significantly associated with better OS (HR 0.98, 95% CI 0.96\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.064) and PFS (HR 0.98, 95% CI 0.95\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.024). Omission of TMZ predicted inferior OS (HR 2.41, 95% CI 1.24\u0026ndash;4.66, p\u0026thinsp;=\u0026thinsp;0.009) and PFS (HR 2.31, 95% CI 1.20\u0026ndash;4.46, p\u0026thinsp;=\u0026thinsp;0.013). Total resection was independently associated with improved OS (HR 0.50, 95% CI 0.26\u0026ndash;0.96, p\u0026thinsp;=\u0026thinsp;0.037), while showing a non-significant trend for PFS (HR 0.62, 95% CI 0.33\u0026ndash;1.17, p\u0026thinsp;=\u0026thinsp;0.14). Sensitivity analyses confirmed the robustness of the models, with no relevant violations of the proportional hazards assumption (global p\u0026thinsp;=\u0026thinsp;0.164 for OS; p\u0026thinsp;=\u0026thinsp;0.086 for PFS).\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003eIn this real-world cohort of elderly GBM patients, survival outcomes remained poor despite multimodal therapy. Independent predictors of improved outcomes included younger age, female sex, higher performance status, total resection, and temozolomide therapy. Sensitivity analyses confirmed the robustness of the models, underscoring the prognostic relevance of established clinical and treatment-related factors and highlighting the need for individualized treatment approaches in this vulnerable population.\u003c/p\u003e","manuscriptTitle":"Real-World Evidence on the Management and Outcomes of Glioblastoma in Elderly Patients: A Monocentric Retrospective Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-10 00:38:52","doi":"10.21203/rs.3.rs-8011713/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"329066147128779960416111847906284981082","date":"2025-12-13T22:31:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-10T14:51:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54428893382558000593704978557204289009","date":"2025-12-10T10:08:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-08T05:44:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-12T10:21:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-12T07:59:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-12T07:57:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-11-02T14:40:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"55a00eca-956e-4271-ac62-10de12e05e66","owner":[],"postedDate":"December 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-10T00:38:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-10 00:38:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8011713","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8011713","identity":"rs-8011713","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}