Differences in tumor size, clinical, demographic, and socioeconomic profiles of central nervous system tumors among a racially diverse cohort: A retrospective case-control study

Background

One avenue to improve outcomes among brain tumor patients involves the mitigation of healthcare disparities. Investigating clinical differences among brain tumors across socioeconomic and demographic strata, such can aid in healthcare disparity identification and, by extension, outcome improvement.

Methods

Utilizing a racially diverse population from Hawaii, 323 cases of brain tumors (meningiomas, gliomas, schwannomas, pituitary adenomas, and metastases) were matched by age, sex, and race to 651 controls to investigate the associations between tumor type and various demographic, socioeconomic, and medical comorbidities. Tumor size at the time of diagnosis was also compared across demographic groups.

Results

At the time of diagnosis for benign meningiomas, Native Hawaiians and Pacific Islanders (NHPI; P < 0.05), Asians, and Hispanics exhibited nearly two-fold larger tumor volumes than Whites. For gliomas, NHPI similarly presented with larger tumor volumes relative to Whites (P = 0.04) and Asians (P = 0.02), while for vestibular schwannomas, NHPI had larger tumor sizes compared to Asians (P < 0.05). Benign meningiomas demonstrated greater odds of diagnosis (P < 0.05) among Native American or Alaskan Natives, patients comorbid with obesity class I, hypertension, or with a positive Alcohol Use Disorders Identification Test-Consumption (AUDIT-C). Malignant meningiomas demonstrated greater odds (P < 0.05) among patients from higher median household income and urban geography. Gliomas overall exhibited increased odds (P < 0.05) of diagnosis among Whites and reduced odds among Asians, with greater comorbidity with obesity class III; for glioblastoma specifically, there were reduced odds of asthma diagnosis. Patients with vestibular schwannomas were at increased odds (P < 0.05) of being from the highest income quartile and having a positive AUDIT-C, yet reduced odds of psychiatric disorders. Pituitary adenomas exhibited reduced odds of diagnosis among Whites, yet greater odds among NHPI, military personnel, obesity class I, and psychiatric disorders. Intracranial metastases were more common in patients with pre-obesity, asthma, a positive AUDIT-C, and living in more affluent regions. Benign meningiomas are most often presented with seizures, while malignant meningiomas have the addition of cognitive difficulty. Gliomas often present with seizures, cognitive difficulty, dizziness/nausea/vomiting (DNV), vestibular schwannomas with DNV, and metastases with seizures.

Conclusion

Brain tumors exhibit unique sociodemographic disparities and clinical comorbidities, which may have implications for diagnosis, treatment, and healthcare policy.

Fear of Cancer Recurrence in Adult Survivors of Childhood Cancer

Importance

Fear of cancer recurrence is common among survivors of adult-onset cancer and associated with increased distress, functional impairment, and health care utilization. However, little is known about the prevalence and risk factors of fear of cancer recurrence among adult survivors of childhood cancer who are also at high risk for subsequent malignant neoplasms.

Objective

To characterize the prevalence of and risk factors for clinically significant fear of cancer recurrence in adult survivors of childhood cancer.

Design, Setting, and Participants

This cross-sectional investigation included participants recruited from the Childhood Cancer Survivor Study, a retrospective cohort study of long-term childhood cancer survivors treated at 31 institutions between 1970 and 1999 across North America. Participants were recruited and completed psychosocial measures via online survey between October 2018 and April 2019. Cancer and treatment-related variables were abstracted from medical records. Data were analyzed from May 2023 to July 2024.

Main Outcomes and Measures

Clinically significant fear of cancer recurrence was assessed via the Fear of Cancer Recurrence Inventory-Short Form. Poisson regression models estimated prevalence ratios (PRs) with 95% CIs adjusted for age and sex to examine the associations of demographic, disease, treatment, and psychosocial variables with fear of cancer recurrence.

Results

The final sample included 229 adult survivors of childhood cancer (115 female [50.2%]; mean [SD] age, 39.6 [9.9] years; mean [SD] time since diagnosis, 31.7 [8.4] years). Among survivors, 38 (16.6%; 95% CI, 11.6%-21.6%) reported clinically significant fear of cancer recurrence, and an additional 36 (15.7%) reported high fear of cancer recurrence. Clinically significant fear of cancer recurrence was associated with unemployment (PR, 2.5; 95% CI, 1.3-4.8), presence of neurologic chronic health conditions (PR, 3.3; 95% CI, 1.8-6.1), treatment with pelvic radiation (PR, 2.9; 95% CI, 1.5-5.6), and amputation or limb sparing surgery (PR, 2.4; 95% CI, 1.2-4.9). Higher risk of clinically significant fear of cancer recurrence was also associated with having either elevated anxiety or depression (PR, 2.6; 95% CI, 1.2-5.9), having both elevated (PR, 3.2; 95% CI, 1.2-8.4), and perceived poor health status (PR, 3.0; 95% CI, 3.1-9.7).

Conclusions and Relevance

Decades following treatment, one-third of childhood cancer survivors in this study reported elevated fear their cancer will recur or a subsequent malignant neoplasm will develop. Findings suggest that fear of cancer recurrence should be routinely screened, and clinically significant symptoms intervened upon as a part of survivorship care.

Systematic Review of WHO Grade 4 Astrocytoma in the Cerebellopontine Angle: The Impact of Anatomic Corridor on Treatment Options and Outcomes

Background  Despite advances in multimodal oncologic therapies and molecular genetics, overall survival (OS) in patients with high-grade astrocytomas remains poor. We present an illustrative case and systematic review of rare, predominantly extra-axial World Health Organization (WHO) grade 4 astrocytomas located within the cerebellopontine angle (CPA) and explore the impact of anatomic location on diagnosis, management, and outcomes. Methods  A systematic review of adult patients with predominantly extra-axial WHO grade 4 CPA astrocytomas was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines through December 2022. Results  Eighteen articles were included comprising 21 astrocytomas: 13 exophytic tumors arising from the cerebellopontine parenchyma and 8 tumors originating from a cranial nerve root entry zone. The median OS was 15 months with one-third of cases demonstrating delayed diagnosis. Gross total resection, molecular genetic profiling, and use of ancillary treatment were low. We report the only patient with an integrated isocitrate dehydrogenase 1 (IDH-1) mutant diagnosis, who, after subtotal resection and chemoradiation, remains alive at 40 months without progression. Conclusion  The deep conical-shaped corridor and abundance of eloquent tissue of the CPA significantly limits both surgical resection and utility of device-based therapies in this region. Prompt diagnosis, molecular characterization, and systemic therapeutic advances serve as the predominant means to optimize survival for patients with rare skull base astrocytomas.

The Therapeutic Values of IL-7/IL-7R and the Recombinant Derivatives in Glioma: A Narrative Review

Interleukin-7 (IL-7) is essential for maintaining the immune system's defense functions by regulating the development and homeostasis of lymphocytes. Findings have shown the high efficacy of IL-7/IL-7 receptor (IL-7R)-based immunotherapy on various malignancies, with confirmation in both animal models and humans. In recent years, the progression-free survival and overall survival of patients suffering from gliomas significantly increased by introducing C7R-expressing chimeric antigen receptor (CAR)-T cells and long-acting IL-7 agonists such as NT-I7 (rhIL-7-hyFc, Efineptakin alfa). However, the effect of IL-7-based immunotherapies on the resistance of tumor cells to chemotherapy (when used simultaneously with chemotherapy agents) is still ambiguous and requires further studies. This article first reviews the pathophysiological roles of IL-7/IL-7R in tumors, focusing on gliomas. Subsequently, it discusses the therapeutic values of IL-7/IL-7R and the recombinant derivatives in gliomas.

Upstaging and Downstaging in Gliomas-Clinical Implications for the Fifth Edition of the World Health Organization Classification of Tumors of the Central Nervous System

In 2021, the 5th edition of the WHO Classification of Tumors of the Central Nervous System (WHO-CNS5) was published as the sixth volume of the international standard for brain and spinal cord tumor classification. The most remarkable practical change in the current classification involves grading gliomas according to molecular characterization. IDH mutant (10%) and IDH wild-type tumors (90%) are two different entities that possess unique biological features and various clinical outcomes regarding treatment response and overall survival. This article presents two comparative cases that highlight the clinical importance of these new classification standards. The first clinical case aimed to provide a comprehensive argument for determining the IDH status in tumors initially appearing as low-grade astrocytoma upon histologic examination, thus underlining the importance of the WHO-CNS5. The second case showed the implications of the histologic overdiagnosis of glioblastoma using the previous classification system with a treatment span of 7 years that proceeded through full-dose re-irradiation up to metronomic therapy. The new WHO-CNS5 classification significantly impacted complex neurooncological cases, thus changing the initial approach to a more precise therapeutic management.

Brain Tumor Classification Using a Combination of Variational Autoencoders and Generative Adversarial Networks

Brain tumors are a pernicious cancer with one of the lowest five-year survival rates. Neurologists often use magnetic resonance imaging (MRI) to diagnose the type of brain tumor. Automated computer-assisted tools can help them speed up the diagnosis process and reduce the burden on the health care systems. Recent advances in deep learning for medical imaging have shown remarkable results, especially in the automatic and instant diagnosis of various cancers. However, we need a large amount of data (images) to train the deep learning models in order to obtain good results. Large public datasets are rare in medicine. This paper proposes a framework based on unsupervised deep generative neural networks to solve this limitation. We combine two generative models in the proposed framework: variational autoencoders (VAEs) and generative adversarial networks (GANs). We swap the encoder-decoder network after initially training it on the training set of available MR images. The output of this swapped network is a noise vector that has information of the image manifold, and the cascaded generative adversarial network samples the input from this informative noise vector instead of random Gaussian noise. The proposed method helps the GAN to avoid mode collapse and generate realistic-looking brain tumor magnetic resonance images. These artificially generated images could solve the limitation of small medical datasets up to a reasonable extent and help the deep learning models perform acceptably. We used the ResNet50 as a classifier, and the artificially generated brain tumor images are used to augment the real and available images during the classifier training. We compared the classification results with several existing studies and state-of-the-art machine learning models. Our proposed methodology noticeably achieved better results. By using brain tumor images generated artificially by our proposed method, the classification average accuracy improved from 72.63% to 96.25%. For the most severe class of brain tumor, glioma, we achieved 0.769, 0.837, 0.833, and 0.80 values for recall, specificity, precision, and F1-score, respectively. The proposed generative model framework could be used to generate medical images in any domain, including PET (positron emission tomography) and MRI scans of various parts of the body, and the results show that it could be a useful clinical tool for medical experts.