A Model to Predict the Feasibility of Concurrent Chemoradiotherapy With Temozolomide in Glioblastoma Multiforme Patients Over Age 65

Management of glioblastoma in elderly patients: A review of the literature

High grade gliomas are the most common primary aggressive brain tumours with a very poor prognosis and a median survival of less than 2 years. The standard management protocol of newly diagnosed glioblastoma patients involves surgery followed by radiotherapy, chemotherapy in the form of temozolomide and further adjuvant temozolomide. The recent advances in molecular profiling of high-grade gliomas have further enhanced our understanding of the disease. Although the management of glioblastoma is standardised in newly diagnosed adult patients there is a lot of debate regarding the best treatment approach for the newly diagnosed elderly glioblastoma patients. In this review article we attempt to summarise the findings regarding surgery, radiotherapy, chemotherapy, and their combination in order to offer the best possible management modality for this group of patients. Elderly patients 65-70 with an excellent functional level could be considered as candidates for the standards treatment consisting of surgery, standard radiotherapy with concomitant and adjuvant temozolomide. Similarly, elderly patients above 70 with good functional status could receive the above with the exception of receiving a shorter course of radiotherapy instead of standard. In elderly GBM patients with poorer functional status and MGMT promoter methylation temozolomide chemotherapy can be considered. For elderly patients who cannot tolerate chemotherapy, hypofractionated radiotherapy is an option. In contrast to the younger adult patients, it seems that a careful individualised approach is a key element in deciding the best treatment options for this group of patients.

Comprehensive multimodal deep learning survival prediction enabled by a transformer architecture: A multicenter study in glioblastoma

Background

This research aims to improve glioblastoma survival prediction by integrating MR images, clinical, and molecular-pathologic data in a transformer-based deep learning model, addressing data heterogeneity and performance generalizability.

Methods

We propose and evaluate a transformer-based nonlinear and nonproportional survival prediction model. The model employs self-supervised learning techniques to effectively encode the high-dimensional MRI input for integration with nonimaging data using cross-attention. To demonstrate model generalizability, the model is assessed with the time-dependent concordance index (Cdt) in 2 training setups using 3 independent public test sets: UPenn-GBM, UCSF-PDGM, and Rio Hortega University Hospital (RHUH)-GBM, each comprising 378, 366, and 36 cases, respectively.

Results

The proposed transformer model achieved a promising performance for imaging as well as nonimaging data, effectively integrating both modalities for enhanced performance (UCSF-PDGM test-set, imaging Cdt 0.578, multimodal Cdt 0.672) while outperforming state-of-the-art late-fusion 3D-CNN-based models. Consistent performance was observed across the 3 independent multicenter test sets with Cdt values of 0.707 (UPenn-GBM, internal test set), 0.672 (UCSF-PDGM, first external test set), and 0.618 (RHUH-GBM, second external test set). The model achieved significant discrimination between patients with favorable and unfavorable survival for all 3 datasets (log-rank P 1.9 × 10-8, 9.7 × 10-3, and 1.2 × 10-2). Comparable results were obtained in the second setup using UCSF-PDGM for training/internal testing and UPenn-GBM and RHUH-GBM for external testing (Cdt 0.670, 0.638, and 0.621).

Conclusions

The proposed transformer-based survival prediction model integrates complementary information from diverse input modalities, contributing to improved glioblastoma survival prediction compared to state-of-the-art methods. Consistent performance was observed across institutions supporting model generalizability.

Bilateral Laser Interstitial Thermal Therapy for Butterfly Gliomas Compared With Needle Biopsy: A Preliminary Survival Study

BACKGROUND AND OBJECTIVES

Bilateral/butterfly glioblastoma (bGBM) has a poor prognosis. Resection of these tumors is limited due to severe comorbidities that arise from surgical procedures. Laser interstitial thermal therapy (LITT) offers a minimally invasive cytoreductive therapy for deep-seated tumors such as bGBM. The objective of this study was to evaluate the safety of bilateral LITT in patients with bGBM.

METHODS

Medical records of all consecutive patients diagnosed with bGBM by a single surgeon at a single institution from January 2014 to August 2022 were reviewed. Clinical, safety, and radiographic volumetric data were obtained. In addition, an exploratory analysis of survival was performed.

RESULTS

A total of 25 patients were included; 14 underwent biopsy only, and 11 underwent biopsy + LITT (7 underwent bilateral and 4 underwent unilateral LITT). No (0%) intraoperative or postoperative complications were recorded in the treatment group. Tumor volume negatively correlated with extent of treatment (r 2 = 0.44, P = .027). The median progression-free survival was 2.8 months in the biopsy-only group and 5.5 months in the biopsy + LITT group ( P = .026). The median overall survival was 4.3 months in the biopsy-only group and 10.3 months in the biopsy + LITT group ( P = .035).

CONCLUSION

Bilateral LITT for bGBM can be safely performed and shows early improvement of the progression-free survival and long-term survival outcomes of these patients.

Loss of sphingosine kinase 2 protects against cisplatin-induced kidney injury

Cisplatin is an established chemotherapeutic drug for treatment of solid-organ cancers and is the primary drug used in the treatment of head and neck cancer; however, cisplatin-induced nephrotoxicity largely limits its clinical use. Inhibition of sphingosine kinase 2 (SphK2) has been demonstrated to alleviate various kidney diseases. Therefore, we hypothesized that inhibition of SphK2 could also protect against cisplatin-induced nephrotoxicity. Results from the present study showed that the SphK2 inhibitor ABC294640 or knockdown of SphK2 by siRNA blocked the cisplatin-induced increase of cellular injury markers (neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, and cleaved caspase-3) by Western blot analysis in HK-2 cells, a human renal tubular cell line. In addition, SphK2 inhibition blocked cisplatin-induced activation of NF-κB by Western blot analysis and immunostaining analysis. Furthermore, SphK2 inhibition suppressed cisplatin-induced increases of proinflammatory markers (NLR family pyrin domain containing 3, interleukin-1β, and interleukin-6). Genetic deletion of the SphK2 gene in mice further confirmed that inhibition of SphK2 protected against cisplatin-induced kidney damage in vivo. Compared with wild-type mice, SphK2 knockout mice exhibited less renal dysfunction and reduced promotion of kidney injury markers, inflammatory factors, tubular morphology damage, and fibrotic staining. At the same time, the SphK2 inhibitor ABC294640 failed to interfere with the activity of cisplatin or radiation in two cell culture models of head and neck cancer. It is concluded that inhibition of Sphk2 protects against cisplatin-induced kidney injury. SphK2 may be used as a potential therapeutic target for the prevention or treatment of cisplatin-induced kidney injury.NEW & NOTEWORTHY The present study provides new findings that sphingosine kinase 2 (SphK2) is highly expressed in renal tubules, cisplatin treatment increases the expression of SphK2 in proximal tubular cells and kidneys, and inhibition of SphK2 alleviates cisplatin-induced kidney injury by suppressing the activation of NF-κB, production of inflammatory factors, and apoptosis. SphK2 may serve as a potential therapeutic target for the prevention or treatment of cisplatin-induced nephrotoxicity.

Sex-Specific Differences in Glioblastoma

Sex differences have been well identified in many brain tumors. Even though glioblastoma (GBM) is the most common primary malignant brain tumor in adults and has the worst outcome, well-established differences between men and women are limited to incidence and outcome. Little is known about sex differences in GBM at the disease phenotype and genetical/molecular level. This review focuses on a deep understanding of the pathophysiology of GBM, including hormones, metabolic pathways, the immune system, and molecular changes, along with differences between men and women and how these dimorphisms affect disease outcome. The information analyzed in this review shows a greater incidence and worse outcome in male patients with GBM compared with female patients. We highlight the protective role of estrogen and the upregulation of androgen receptors and testosterone having detrimental effects on GBM. Moreover, hormones and the immune system work in synergy to directly affect the GBM microenvironment. Genetic and molecular differences have also recently been identified. Specific genes and molecular pathways, either upregulated or downregulated depending on sex, could potentially directly dictate GBM outcome differences. It appears that sexual dimorphism in GBM affects patient outcome and requires an individualized approach to management considering the sex of the patient, especially in relation to differences at the molecular level.

Elderly patients with newly diagnosed glioblastoma: can preoperative imaging descriptors improve the predictive power of a survival model?

The purpose of this study was to identify independent prognostic factors among preoperative imaging features in elderly glioblastoma patients and to evaluate whether these imaging features, in addition to clinical features, could enhance the predictive power of survival models. This retrospective study included 108 patients ≥65 years of age with newly diagnosed glioblastoma. Preoperative clinical features (age and KPS), postoperative clinical features (extent of surgery and postoperative treatment), and preoperative MRI features were assessed. Univariate and multivariate cox proportional hazards regression analyses for overall survival were performed. The integrated area under the receiver operating characteristic curve (iAUC) was calculated to evaluate the added value of imaging features in the survival model. External validation was independently performed with 40 additional patients ≥65 years of age with newly diagnosed glioblastoma. Eloquent area involvement, multifocality, and ependymal involvement on preoperative MRI as well as clinical features including age, preoperative KPS, extent of resection, and postoperative treatment were significantly associated with overall survival on univariate Cox regression. On multivariate analysis, extent of resection and ependymal involvement were independently associated with overall survival and preoperative KPS showed borderline significance. The model with both preoperative clinical and imaging features showed improved prediction of overall survival compared to the model with preoperative clinical features (iAUC, 0.670 vs. 0.600, difference 0.066, 95% CI 0.021-0.121). Analysis of the validation set yielded similar results (iAUC, 0.790 vs. 0.670, difference 0.123, 95% CI 0.021-0.260), externally validating this observation. Preoperative imaging features, including eloquent area involvement, multifocality, and ependymal involvement, in addition to clinical features, can improve the predictive power for overall survival in elderly glioblastoma patients.

Adherence to oral cancer therapy in older adults: The International Society of Geriatric Oncology (SIOG) taskforce recommendations

There is an increasing trend towards using oral systemic therapy in patients with cancer. Compared to parenteral therapy, oral cancer agents offer convenience, have similar efficacy, and are preferred by patients, consequently making its use appealing in older adults. However, adherence is required to ensure its efficacy and to avoid compromising treatment outcomes, especially when the treatment goal is curative, or in case of symptomatic/rapidly progressing disease, where dose-intensity is important. This opens a new challenge for clinicians, as optimizing patient adherence is challenging, particularly due to lack of consensus and scarcity of available clinical evidence. This manuscript aims to review the impact of age-related factors on adherence, summarize the evidence on adherence, recommend methods for selecting patients suitable for oral cancer agents, and advise monitoring interventions to promote adherence to treatment.