Fecci, Peter E.

Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factors remains limited. To test the interactive effects of demographic, socioeconomic, and oncologic variables on trial enrollment, we designed boosted neural networks (BNNs) for all glioma patients ( n = 1042), women ( n = 445, 42.7%), and minorities ( n = 151, 14.5%) and externally validated these models [whole cohort, n = 230; women, n = 89 (38.7%); minority, n = 66 (28.7%)]. For the whole-cohort BNN, the most influential variables on enrollment were oncologic variables, including KPS [total effect (TE), 0.327], chemotherapy (TE, 0.326), tumor location (TE, 0.322), and seizures (TE, 0.239). The women-only BNN exhibited a similar trend. Conversely, for the minority-only BNN, socioeconomic variables [insurance status (TE, 0.213), occupation classification (TE, 0.204), and employment status (TE, 0.150)] were most influential. These results may help prioritize patient-specific initiatives to increase accrual.

Abstract BACKGROUND Despite changes in national policy, women and minority patients remain under-accrued in glioma clinical trials. Supervised machine learning may serve as a novel approach to understanding which variables and their complex interplay most influence enrollment for underrepresented patients. We aimed to design and externally validate machine learning models to predict therapeutic clinical trial enrollment for a) all patients, b) women, and c) NIH-designated minority patients with low- and high-grade glioma. METHODS In a 20-year retrospective cohort of 1042 adult patients with low- and high-grade glioma, boosted neural network (BNN) models for the whole, women, and minority cohorts were used to analyze the combined effects of demographic, socioeconomic, and oncologic variables on clinical trial enrollment. These models were validated using an external cohort (n=103). RESULTS In the development cohort (445 [42.7%] women; 151 [14.5%] minorities; median age, 51.5 [interquartile range: 39.4-62.5] years), 350 patients (33.6%) enrolled in a therapeutic clinical trial. The whole cohort BNN (AUC: 0.827, misclassification rate (MR): 0.175), the women cohort BNN (AUC: 0.895, MR: 0.125), and the minority cohort BNN (AUC: 0.983, MR: 0.053) models accurately predicted trial enrollment on external validation. For the whole cohort and women models, several demographic (race, ethnicity, minority status, sex), socioeconomic (insurance, employment status), and oncologic variables (seizure, chemotherapy, KPS, WHO grade, tumor lobe) were equally influential (Main effect (ME): 1.000, Total effect (TE): 1.000) on enrollment. For the minority model, socioeconomic variables including insurance status (ME: 0.089, TE: 0.417) and occupation classification (ME: 0.087, TE: 0.381) drove enrollment. CONCLUSION We designed and externally validated the first machine learning model for predicting therapeutic clinical trial enrollment for patients with diffuse glioma. Model features driving trial enrollment varied for underrepresented patients. These results may help prioritize personalized patient-specific initiatives to address barriers to equitable patient accrual.

AbstractBackgroundThe nervous and immune systems interact in a reciprocal manner, both under physiologic and pathologic conditions. Literature spanning various CNS pathologies including brain tumors, stroke, traumatic brain injury and de-myelinating diseases describes a number of associated systemic immunologic changes, particularly in the T-cell compartment. These immunologic changes include severe T-cell lymphopenia, lymphoid organ contraction, and T-cell sequestration within the bone marrow.MethodsWe performed an in-depth systematic review of the literature and discussed pathologies that involve brain insults and systemic immune derangements.ConclusionsIn this review, we propose that the same immunologic changes hereafter termed ‘systemic immune derangements’, are present across CNS pathologies and may represent a novel, systemic mechanism of immune privilege for the CNS. We further demonstrate that systemic immune derangements are transient when associated with isolated insults such as stroke and TBI but persist in the setting of chronic CNS insults such as brain tumors. Systemic immune derangements have vast implications for informed treatment modalities and outcomes of various neurologic pathologies.

Abstract Treatment options for glioblastoma remain limited, particularly for those who are not eligible for traditional resection, whether due to lesion location or inability to tolerate open craniotomy. Maximal-safe resection followed by radiation with concurrent and adjuvant temozolomide offers the best outcomes for patients. Unfortunately, not all tumors are amenable to conventional surgical resection at the time of diagnosis with only about 1/3 of patients able to receive a gross-total resection and 15-25% of patients receiving biopsy only, thus reducing their projected overall survival to 9 months. Laser interstitial thermal therapy (LITT) is a minimally invasive, cytoreductive tool, that has demonstrated safety as a surgical approach to treat primary brain tumors. METHODS Data from LAANTERN prospective multicenter registry (NCT02392078) was analyzed to determine clinical outcomes for patients with new and recurrent IDH wild-type glioblastoma (N=89). Demographics, intraprocedural data, adverse events, KPS, health-economics, and survival data were prospectively collected then analyzed separately for newly diagnosed GBM (N=29) and recurrent GBM (N=60). RESULTS Median overall-survival was 9.73 months (95% CI: 5.16, 15.91) for newly diagnosed patients and median post-procedure survival was 8.97 (6.94, 12.36) months for recurrent patients. Median overall-survival for newly diagnosed patients receiving post-LITT chemoradiotherapy was 16.14 months (6.11, not reached). The median length of hospital stay was 50 hours and 80% of patients were discharged to home. CONCLUSIONS LITT offers an effective cytoreductive approach for patients with newly diagnosed and recurrent IDH wild-type glioblastoma. Importantly, its use in newly diagnosed patients who receive post-LITT chemoradiotherapy leads to a median OS similar to that of patients treated with conventional surgical resection. LITT remains an important alternative for patients with inoperable tumors or those not amenable to resection. Enrollment in LAANTERN is ongoing and these cohorts will be revisited as data continues to mature. Benefits beyond cytoreduction are also being actively explored.

Abstract Background Few studies have assessed the impact of race on short-term patient outcomes in the brain metastasis population. The goal of this study is to evaluate the association of race with inpatient clinical presentation, treatment, in-hospital complications, and in-hospital mortality rates for patients with brain metastases (BM). Method Using data collected from the National Inpatient Sample between 2004 and 2014, we retrospectively identified adult patients with a primary diagnosis of BM. Outcomes included nonroutine discharge, prolonged length of stay (pLOS), in-hospital complications, and mortality. Results Minority (Black, Hispanic/other) patients were less likely to receive surgical intervention compared to White patients (odds ratio [OR] 0.70; 95% confidence interval [CI] 0.66–0.74, p < 0.001; OR 0.88; 95% CI 0.84–0.93, p < 0.001). Black patients were more likely to develop an in-hospital complication than White patients (OR 1.35, 95% CI 1.28–1.41, p < 0.001). Additionally, minority patients were more likely to experience pLOS than White patients (OR 1.48; 95% CI 1.41–1.57, p < 0.001; OR 1.34; 95% CI 1.27–1.42, p < 0.001). Black patients were more likely to experience a nonroutine discharge (OR 1.25; 95% CI 1.19–1.31, p < 0.001) and higher in-hospital mortality than White (OR 1.13; 95% CI 1.03–1.23, p = 0.008). Conclusion Our analysis demonstrated that race is associated with disparate short-term outcomes in patients with BM. More efforts are needed to address these disparities, provide equitable care, and allow for similar outcomes regardless of care.

Abstract Background Treatment options for unresectable new and recurrent glioblastoma remain limited. Laser ablation has demonstrated safety as a surgical approach to treating primary brain tumors. The LAANTERN prospective multicenter registry (NCT02392078) data were analyzed to determine clinical outcomes for patients with new and recurrent IDH wild-type glioblastoma. Methods Demographics, intraprocedural data, adverse events, KPS, health economics, and survival data were prospectively collected and then analyzed on IDH wild-type newly diagnosed and recurrent glioblastoma patients who were treated with laser ablation at 14 US centers between January 2016 and May 2019. Data were monitored for accuracy. Statistical analysis included individual variable summaries, multivariable differences in survival, and median survival numbers. Results A total of 29 new and 60 recurrent IDH wild-type WHO grade 4 glioblastoma patients were treated. Positive MGMT promoter methylation status was present in 5/29 of new and 23/60 of recurrent patients. Median physician-estimated extent of ablation was 91%-99%. Median overall survival (OS) was 9.73 months (95% confidence interval: 5.16, 15.91) for newly diagnosed patients and median post-procedure survival was 8.97 months (6.94, 12.36) for recurrent patients. Median OS for newly diagnosed patients receiving post-LITT chemo/radiation was 16.14 months (6.11, not reached). Factors associated with improved survival were MGMT promoter methylation, adjuvant chemotherapy within 12 weeks, and tumor volume <3 cc. Conclusions Laser ablation is a viable option for patients with new and recurrent glioblastoma. Median OS for IDH wild-type newly diagnosed glioblastoma is comparable to outcomes observed in other tumor resection studies when those patients undergo radiation and chemotherapy following LITT.