Repurposing mebendazole against triple-negative breast cancer CNS metastasis.

PURPOSE: Triple-negative breast cancer (TNBC) often metastasizes to the central nervous system (CNS) and has the highest propensity among breast cancer subtypes to develop leptomeningeal disease (LMD). LMD is a spread of cancer into leptomeningeal space that speeds up the disease progression and severely aggravates the prognosis. LMD has limited treatment options. We sought to test whether the common anti-helminthic drug mebendazole (MBZ) may be effective against murine TNBC LMD. METHODS: A small-molecule screen involving TNBC cell lines identified benzimidazoles as potential therapeutic agents for further study. In vitro migration assays were used to evaluate cell migration capacity and the effect of MBZ. For in vivo testing, CNS metastasis was introduced into BALB/c athymic nude mice through internal carotid artery injections of brain-tropic MDA-MB-231-BR or MCF7-BR cells. Tumor growth and spread was monitored by bioluminescence imaging and immunohistochemistry. MBZ was given orally at 50 and 100 mg/kg doses. MBZ bioavailability was assayed by mass spectrometry. RESULTS: Bioinformatic analysis and migration assays revealed higher migratory capacity of TNBC compared to other breast cancer subtypes. MBZ effectively slowed down migration of TNBC cell line MDA-MB-231 and its brain tropic derivative MDA-MB-231-BR. In animal studies, MBZ reduced leptomeningeal spread, and extended survival in brain metastasis model produced by MDA-MB-231-BR cells. MBZ did not have an effect in the non-migratory MCF7-BR model. CONCLUSIONS: We demonstrated that MBZ is a safe and effective oral agent in an animal model of TNBC CNS metastasis. Our findings are concordant with previous efforts involving MBZ and CNS pathology and support the drug's potential utility to slow down leptomeningeal spread.

Cytodifferentiation of pituitary tumors influences pathogenesis and cavernous sinus invasion.

OBJECTIVE: Pituitary tumors (PTs) continue to present unique challenges given their proximity to the cavernous sinus, whereby invasive behavior can limit the extent of resection and surgical outcome, especially in functional tumors. The aim of this study was to elucidate patterns of cavernoinvasive behavior by PT subtype. METHODS: A total of 169 consecutive first-time surgeries for PTs were analyzed; 45% of the tumors were functional. There were 64 pituitary transcription factor-1 (PIT-1)-expressing, 62 steroidogenic factor-1 (SF-1)-expressing, 38 T-box transcription factor (TPIT)-expressing, and 5 nonstaining PTs. The gold standard for cavernous sinus invasion (CSI) was based on histopathological examination of the cavernous sinus medial wall and intraoperative exploration. RESULTS: Cavernous sinus disease was present in 33% of patients. Of the Knosp grade 3 and 4 tumors, 12 (19%) expressed PIT-1, 7 (11%) expressed SF-1, 8 (21%) expressed TPIT, and 2 (40%), were nonstaining (p = 0.36). PIT-1 tumors had a significantly higher predilection for CSI: 53% versus 24% and 18% for TPIT and SF-1 tumors, respectively (OR 6.08, 95% CI 2.86-13.55; p < 0.001). Microscopic CSI-defined as Knosp grade 0-2 tumors with confirmed invasion-was present in 44% of PIT-1 tumors compared with 7% and 13% of TPIT and SF-1 tumors, respectively (OR 11.72, 95% CI 4.35-35.50; p < 0.001). Using the transcavernous approach to excise cavernous sinus disease, surgical biochemical remission rates for patients with acromegaly, prolactinoma, and Cushing disease were 88%, 87%, and 100%, respectively. The granule density of PIT-1 tumors and corticotroph functional status did not influence CSI. CONCLUSIONS: The likelihood of CSI differed by transcription factor expression; PIT-1-expressing tumors had a higher predilection for invading the cavernous sinus, particularly microscopically, compared with the other tumor subtypes. This elucidates a unique cavernoinvasive behavior absent in cells from other lineages. Innovative surgical techniques, however, can mitigate tumor behavior and achieve robust, reproducible biochemical remission and gross-total resection rates. These findings can have considerable implications on the surgical management and study of PT biology and behavior.

Clinical Outcomes and Cost Differences Between Patients Undergoing Primary Anterior Cervical Discectomy and Fusion Procedures with Private or Medicare Insurance: A Propensity Score-Matched Study.

OBJECTIVE: We assessed whether the insurance type reflects a patient's quality of care after an anterior discectomy and fusion (ACDF) procedure by comparing differences in the postoperative complications, readmission rates, reoperation rates, lengths of hospital stay, and cost of treatment between patients with Medicare versus private insurance. METHODS: Propensity score matching was used to match patient cohorts insured by Medicare and private insurance in the MarketScan Commercial Claims and Encounters Database (2007-2016). Age, sex, year of operation, geographic region, comorbidities, and operative factors were used to match cohorts of patients who had undergone an ACDF procedure. RESULTS: A total of 110,911 patients met the inclusion criteria. Of these patients, 97,543 patients (87.9%) were privately insured and 13,368 patients (12.1%) were insured by Medicare. The propensity score matching algorithm matched 7026 privately insured patients to 7026 Medicare patients. After matching, no significant differences were found in the 90-day postoperative complication rates, lengths of stay, or reoperation rates between the Medicare and privately insured cohorts. The Medicare group had had lower postoperative readmission rates for all time points: 30 days (1.8% vs. 4.6%; P < 0.001), 60 days (2.5% vs. 6.3%; P < 0.001), and 90 days (4.2% vs. 7.7%; P < 0.001). The median payment to physicians was significantly lower for the Medicare group ($3885 vs. $5601; P < 0.001). CONCLUSIONS: In the present study, propensity score matched patients covered by Medicare and private insurance who had undergone an ACDF procedure had had similar treatment outcomes.

A Retrospective Cohort Study of Implantable Pulse Generator Surgical Site Infections After Deep Brain Stimulation Surgery With an Antibacterial Envelope.

INTRODUCTION: Deep brain stimulation (DBS) surgery is an established treatment for many patients with neurologic disease, and a common complication of DBS is surgical site infection (SSI). In 2016, neurosurgeons at our institution began enclosing implantable pulse generators (IPGs) within fully absorbable, antibacterial envelopes in patients who underwent initial DBS implantation. We sought to determine whether the use of antibacterial envelopes reduced IPG-related SSIs. MATERIALS AND METHODS: We performed a retrospective chart review of all adult patients who underwent initial DBS implantation at Stanford Hospital between November 14, 2012, and November 9, 2020. Operative details, perioperative antibiotics, comorbidities, and postoperative complications were extracted for all patients. Univariate and multivariate logistic regression were used to identify factors associated with SSIs within three months of surgery, and interrupted time-series analysis was performed to assess whether the departmental adoption of the antibacterial envelope led to a reduction in IPG SSIs. RESULTS: Of 344 patients who underwent initial IPG implantation with the antibacterial envelope, one developed an SSI within three months of surgery (0.3%), compared with six of 204 patients (2.9%) who underwent the same procedure without the antibacterial envelope (odds ratio: 0.10, 95% CI: 0.01-0.80, p = 0.031). Univariate logistic regression revealed that the antibacterial envelope and 2000-mg intravenous cefazolin perioperatively were associated with reduced SSI risk, whereas no other factors reached statistical significance. After adjusting for comorbidities, no association remained statistically significant. Interrupted time-series analysis showed a reduction in SSIs after 2016, but the effect was not significant. CONCLUSIONS: The adoption of antibacterial envelopes was found to reduce IPG SSIs at the univariate level, but this association did not remain significant after controlling for confounding variables including perioperative antibiotic administration. Although encouraging, this study does not conclusively establish that the use of antibacterial pouches in patients who underwent initial DBS implantation reduces the incidence of IPG SSIs. Future prospective studies that control for confounding variables are necessary to determine the efficacy of antibacterial envelopes in reducing post-DBS infections at the IPG site before clear recommendations can be made.

Predictors of spine metastases at initial presentation of pediatric brain tumor patients: a single-institution study.

PURPOSE: Given the rarity of disseminated disease at the time of initial evaluation for pediatric brain tumor patients, we sought to identify clinical and radiographic predictors of spinal metastasis (SM) at the time of presentation. METHODS: We performed a single-institution retrospective chart review of pediatric brain tumor patients who first presented between 2004 and 2018. We extracted information regarding patient demographics, radiographic attributes, and presenting symptoms. Univariate and multivariate logistic regression was used to estimate the association between measured variables and SMs. RESULTS: We identified 281 patients who met our inclusion criteria, of whom 19 had SM at initial presentation (6.8%). The most common symptoms at presentation were headache (n = 12; 63.2%), nausea/vomiting (n = 16; 84.2%), and gait abnormalities (n = 8; 41.2%). Multivariate models demonstrated that intraventricular and posterior fossa tumors were more frequently associated with SM (OR: 5.28, 95% CI: 1.79-15.59, p = 0.003), with 4th ventricular (OR: 7.42, 95% CI: 1.77-31.11, p = 0.006) and cerebellar parenchymal tumor location (OR: 4.79, 95% CI: 1.17-19.63, p = 0.030) carrying the highest risk for disseminated disease. In addition, evidence of intracranial leptomeningeal enhancement on magnetic resonance imaging (OR: 46.85, 95% CI: 12.31-178.28, p < 0.001) and hydrocephalus (OR: 3.19; 95% CI: 1.06-9.58; p = 0.038) were associated with SM. CONCLUSIONS: Intraventricular tumors and the presence of intracranial leptomeningeal disease were most frequently associated with disseminated disease at presentation. These findings are consistent with current clinical expectations and offer empirical evidence that heightened suspicion for SM may be prospectively applied to certain subsets of pediatric brain tumor patients at the time of presentation.

Comparison of Deep Learning and Classical Machine Learning Algorithms to Predict Postoperative Outcomes for Anterior Cervical Discectomy and Fusion Procedures With State-of-the-art Performance.

STUDY DESIGN: Retrospective cohort. OBJECTIVE: Due to anterior cervical discectomy and fusion (ACDF) popularity, it is important to predict postoperative complications, unfavorable 90-day readmissions, and two-year reoperations to improve surgical decision-making, prognostication, and planning. SUMMARY OF BACKGROUND DATA: Machine learning has been applied to predict postoperative complications for ACDF; however, studies were limited by sample size and model type. These studies achieved ≤0.70 area under the curve (AUC). Further approaches, not limited to ACDF, focused on specific complication types and resulted in AUC between 0.70 and 0.76. MATERIALS AND METHODS: The IBM MarketScan Commercial Claims and Encounters Database and Medicare Supplement were queried from 2007 to 2016 to identify adult patients who underwent an ACDF procedure (N=176,816). Traditional machine learning algorithms, logistic regression, and support vector machines, were compared with deep neural networks to predict: 90-day postoperative complications, 90-day readmission, and two-year reoperation. We further generated random deep learning model architectures and trained them on the 90-day complication task to approximate an upper bound. Last, using deep learning, we investigated the importance of each input variable for the prediction of 90-day postoperative complications in ACDF. RESULTS: For the prediction of 90-day complication, 90-day readmission, and two-year reoperation, the deep neural network-based models achieved AUC of 0.832, 0.713, and 0.671. Logistic regression achieved AUCs of 0.820, 0.712, and 0.671. Support vector machine approaches were significantly lower. The upper bound of deep learning performance was approximated as 0.832. Myelopathy, age, human immunodeficiency virus, previous myocardial infarctions, obesity, and documentary weakness were found to be the strongest variable to predict 90-day postoperative complications. CONCLUSIONS: The deep neural network may be used to predict complications for clinical applications after multicenter validation. The results suggest limited added knowledge exists in interactions between the input variables used for this task. Future work should identify novel variables to increase predictive power.

Rapid intraoperative diagnosis of pediatric brain tumors using Raman spectroscopy: A machine learning approach.

Background: Surgical resection is a mainstay in the treatment of pediatric brain tumors to achieve tissue diagnosis and tumor debulking. While maximal safe resection of tumors is desired, it can be challenging to differentiate normal brain from neoplastic tissue using only microscopic visualization, intraoperative navigation, and tactile feedback. Here, we investigate the potential for Raman spectroscopy (RS) to accurately diagnose pediatric brain tumors intraoperatively. Methods: Using a rapid acquisition RS device, we intraoperatively imaged fresh ex vivo brain tissue samples from 29 pediatric patients at the Lucile Packard Children's Hospital between October 2018 and March 2020 in a prospective fashion. Small tissue samples measuring 2-4 mm per dimension were obtained with each individual tissue sample undergoing multiple unique Raman spectra acquisitions. All tissue samples from which Raman spectra were acquired underwent individual histopathology review. A labeled dataset of 678 unique Raman spectra gathered from 160 samples was then used to develop a machine learning model capable of (1) differentiating normal brain from tumor tissue and (2) normal brain from low-grade glioma (LGG) tissue. Results: Trained logistic regression model classifiers were developed using our labeled dataset. Model performance was evaluated using leave-one-patient-out cross-validation. The area under the curve (AUC) of the receiver-operating characteristic (ROC) curve for our tumor vs normal brain model was 0.94. The AUC of the ROC curve for LGG vs normal brain was 0.91. Conclusions: Our work suggests that RS can be used to develop a machine learning-based classifier to differentiate tumor vs non-tumor tissue during resection of pediatric brain tumors.

Chronic Opioid Use Prior to ACDF Surgery Is Associated with Inferior Postoperative Outcomes: A Propensity-Matched Study of 17,443 Chronic Opioid Users.

OBJECTIVE: Candidates for anterior cervical discectomy and fusion (ACDF) have a higher rate of opioid use than does the public, but studies on preoperative opioid use have not been conducted. We aimed to understand how preoperative opioid use affects post-ACDF outcomes. METHODS: The MarketScan Database was queried from 2007 to 2015 to identify adult patients who underwent an ACDF. Patients were classified into separate cohorts based on the number of separate opioid prescriptions in the year before their ACDF. Ninety-day postoperative complications, postoperative readmission, reoperation, and total inpatient costs were compared between opioid strata. Propensity score-matched patient cohorts were calculated to balance comorbidities across groups. RESULTS: Of 81,671 ACDF patients, 31,312 (38.3%) were nonusers, 30,302 (37.1%) were mild users, and 20,057 (24.6%) were chronic users. Chronic opioid users had a higher comorbidity burden, on average, than patients with less frequent opioid use (P < 0.001). Chronic opioid users had higher rates of postoperative complications (9.1%) than mild opioid users (6.0%) and nonusers (5.3%) (P < 0.001) and higher rates of readmission and reoperation. After balancing opioid nonusers versus chronic opioid users along with demographic characteristics, preoperative comorbidity, and operative characteristics, postoperative complications remained elevated for chronic opioid users relative to opioid nonusers (8.6% vs. 5.7%; P < 0.001), as did rates of readmission and reoperation. CONCLUSIONS: Chronic opioid users had more comorbidities than opioid nonusers and mild opioid users, longer hospitalizations, and higher rates of postoperative complication, readmission, and reoperation. After balancing patients across covariates, the outcome differences persisted, suggesting a durable association between preoperative opioid use and negative postoperative outcomes.

Factors Which Predict Adverse Outcomes in Anterior Cervical Discectomy and Fusion Procedures in the Nonelderly Adult Population.

STUDY DESIGN: Retrospective cohort. OBJECTIVE: The largest published cohort of anterior cervical discectomy and fusion (ACDF) patients was queried to better characterize demographic and operative factors that predict 90-day complication and 2-year reoperation risk. SUMMARY OF BACKGROUND DATA: The MarketScan Database was queried from 2007 to 2016 to identify adult patients until 65 years, who underwent an ACDF procedure using International Classification of Diseases 9th Version (ICD-9) and Current Procedural Terminology (CPT) codes. MarketScan is a national insurance claims database that contains millions of patient records across all 50 states. METHODS: Multivariate logistic regression was used to identify factors associated with complications until 90 days and reoperations until 2 years. RESULTS: Of 138,839 ACDF procedures, 8500 patients (6.1%) experienced a complication within 90 days of the ACDF, and 7433 (5.4%) underwent surgical revision by 2 years. While the use of anterior cervical plating did not predict 2-year reoperation, it was associated with dramatically reduced 90-day complication risk (adjusted odds ratio [aOR]: 0.32; 95% confidence interval [CI]: 0.30-0.34; P <0.001). Upon multivariate analysis, female sex (aOR: 0.83; 95% CI: 0.79-0.87; P <0.001) was associated with decreased risk of 2-year reoperation, while depression predicted a 50% increase in reoperation risk (aOR: 1.51; 95% CI: 1.43-1.59; P <0.001). The single largest factor associated with reoperation risk, however, was the presence of a 90-day postoperative complication (aOR: 1.79; 95% CI: 1.66-1.94; P <0.001). CONCLUSION: Increased patient comorbidities and the use of bone morphogenic protein were found to increase the risk for postoperative complications, while cervical plating was associated with a strong decline in this risk. In addition, poor patient mental health outweighed the adverse of impact of other comorbidities on 2-year revision risk. The presence of a postoperative complication was the key modifiable risk factor associated with reoperation risk. Conclusions from this study may help surgeons better identify high-risk ACDF patients for more careful patient selection, counseling, informed consent, and management.

Development of an integrated risk scale for prediction of shunt placement after neonatal intraventricular hemorrhage.

OBJECTIVE: Neonatal intraventricular hemorrhage (IVH) is a major cause of mortality and morbidity, particularly following premature birth. Even after the acute phase, posthemorrhagic hydrocephalus is a long-term complication, frequently requiring permanent ventriculoperitoneal shunt (VPS) placement. Currently, there are no risk classification methods integrating the constellation of clinical data to predict short- and long-term prognosis in neonatal IVH. To address this need, the authors developed a two-part machine learning approach for predicting short- and long-term outcomes after diagnosis of neonatal IVH. Integrating both maternal and neonatal characteristics, they developed a binary classifier to predict short-term mortality risk and a clinical scale to predict the long-term risk of VPS placement. METHODS: Neonates with IVH were identified from the Optum Clinformatics Data Mart administrative claims database. Matched maternal and childbirth characteristics were obtained for all patients. The primary endpoints of interest were short-term (30 day) mortality and long-term VPS placement. Classification of short-term mortality risk was evaluated using 5 different machine learning approaches and the best-performing method was validated using a withheld validation subset. Prediction of long-term shunt risk was performed using a multivariable Cox regression model with stepwise variable selection, which was subsequently converted to an easily applied integer risk scale. RESULTS: A total of 5926 neonates with IVH were identified. Most patients were born before 32 weeks' gestation (67.2%) and with low birth weight (81.2%). Empirical 30-day mortality risk was 10.9% across all IVH grades and highest among grade IV IVH (34.3%). Among the neonates who survived > 30 days, actuarial 12-month postdiagnosis risk of shunt placement was 5.4% across all IVH grades and 31.3% for grade IV IVH. The optimal short-term risk classifier was a random forest model achieving an area under the receiver operating characteristic curve of 0.882 with important predictors ranging from gestational age to diverse comorbid medical conditions. Selected features for long-term shunt risk stratification were IVH grade, respiratory distress syndrome, disseminated intravascular coagulation, and maternal preeclampsia or eclampsia. An integer risk scale, termed the Shunt Prediction After IVH in Neonates (SPAIN) scale, was developed from these 4 features, which, evaluated on withheld cases, demonstrated improved risk stratification compared with IVH grade alone (Harrell's concordance index 0.869 vs 0.852). CONCLUSIONS: In a large cohort of neonates with IVH, the authors developed a two-pronged, integrated, risk classification approach to anticipate short-term mortality and long-term shunt risk. The application of such approaches may improve the prognostication of outcomes and identification of higher-risk individuals who warrant careful surveillance and early intervention.

A Discussion of Machine Learning Approaches for Clinical Prediction Modeling.

While machine learning has occupied a niche in clinical medicine for decades, continued method development and increased accessibility of medical data have led to broad diversification of approaches. These range from humble regression-based models to more complex artificial neural networks; yet, despite heterogeneity in foundational principles and architecture, the spectrum of machine learning approaches to clinical prediction modeling have invariably led to the development of algorithms advancing our ability to provide optimal care for our patients. In this chapter, we briefly review early machine learning approaches in medicine before delving into common approaches being applied for clinical prediction modeling today. For each, we offer a brief introduction into theory and application with accompanying examples from the medical literature. In doing so, we present a summarized image of the current state of machine learning and some of its many forms in medical predictive modeling.

Changes in Orthopaedic diagnoses during the COVID-19 pandemic.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has been accompanied by significant reductions in patient volumes for non-COVID-19-related conditions ranging from acute coronary syndrome to ischemic strokes to acute trauma. However, the impact of the COVID-19 pandemic on patient volumes for a broad range of orthopedic conditions remains unknown. The purpose of this study was to investigate the association of the COVID-19 pandemic with changes in patient volumes of 35 emergent (e.g. dislocations, open fractures), urgent (e.g. fractures), and nonurgent orthopedic conditions (e.g. osteoarthritis, sprains). METHODS: A retrospective interrupted time-series analysis of patient volumes was conducted for 35 orthopedic conditions based on ICD-10 diagnosis codes. Patient hospitalizations and new problem visits were aggregated across two institutions in New York state, including one urban tertiary care orthopedic hospital, one urban academic medical center, and all state outpatient facilities affiliated with the orthopedic institution. Patient volumes in the COVID-19 peak period (03/2020-05/2020) and COVID-19 recovery period (06/2020-10/2020) were compared against pre-COVID-19 vol (01/2018-02/2020). RESULTS: Overall, 169,047 cases were included in the analysis across 35 conditions with 3775 emergent cases, 6376 urgent cases, and 158,896 nonurgent cases. During the COVID-19 peak period, patient caseloads for 1 out of 7 emergent conditions (p = 0.02) and 26 out of 28 urgent and nonurgent conditions (p < 0.05) were significantly reduced compared to the pre-COVID-19 period. During the COVID-19 recovery period, patient volumes in 3 out of 13 emergent and urgent conditions (p < 0.03) and 11 out of 22 nonurgent conditions (p < 0.04) were decreased compared to pre-COVID-19 vol. CONCLUSIONS: This study found that the pandemic was associated with considerable changes in patient patterns for non-COVID-19 orthopedic conditions. The long-term effects of patient volume reductions on both patient outcomes and orthopedic health systems remain to be seen. LEVEL OF EVIDENCE: Cohort study; level of evidence IV.

Risk of secondary neoplasms after external-beam radiation therapy treatment of pediatric low-grade gliomas: a SEER analysis, 1973-2015.

OBJECTIVE: Although past studies have associated external-beam radiation therapy (EBRT) with higher incidences of secondary neoplasms (SNs), its effect on SN development from pediatric low-grade gliomas (LGGs), defined as WHO grade I and II gliomas of astrocytic or oligodendrocytic origin, is not well understood. Utilizing a national cancer registry, the authors sought to characterize the risk of SN development after EBRT treatment of pediatric LGG. METHODS: A total of 1245 pediatric patient (aged 0-17 years) records from 1973 to 2015 were assembled from the Surveillance, Epidemiology, and End Results (SEER) database. Univariable and multivariable subdistribution hazard regression models were used to evaluate the prognostic impact of demographic, tumor, and treatment-related covariates. Propensity score matching was used to balance baseline characteristics. Cumulative incidence analyses measured the time to, and rate of, SN development, stratified by receipt of EBRT and controlled for competing mortality risk. The Fine and Gray semiparametric model was used to estimate future SN risk in EBRT- and non-EBRT-treated pediatric patients. RESULTS: In this study, 366 patients received EBRT and 879 did not. Forty-six patients developed SNs after an LGG diagnosis, and 27 of these patients received EBRT (OR 3.61, 95% CI 1.90-6.95; p < 0.001). For patients alive 30 years from the initial LGG diagnosis, the absolute risk of SN development in the EBRT-treated cohort was 12.61% (95% CI 8.31-13.00) compared with 4.99% (95% CI 4.38-12.23) in the non-EBRT-treated cohort (p = 0.013). Cumulative incidence curves that were adjusted for competing events still demonstrated higher rates of SN development in the EBRT-treated patients with LGGs. After matching across available covariates and again adjusting for the competing risk of mortality, a clear association between EBRT and SN development remained (subhazard ratio 2.26, 95% CI 1.21-4.20; p = 0.010). CONCLUSIONS: Radiation therapy was associated with an increased risk of future SNs for pediatric patients surviving LGGs. These data suggest that the long-term implications of EBRT should be considered when making treatment decisions for this patient population.

Management of brain tumors presenting in pregnancy: a case series and systematic review.

Patients who present with brain tumors during pregnancy require unique imaging and neurosurgical, obstetrical, and anesthetic considerations. Here, we review the literature and discuss the management of patients who present with brain tumors during pregnancy. Between 2009 and 2019, 9 patients were diagnosed at our institution with brain tumors during pregnancy. Clinical information was extracted from the electronic medical records. The median age at presentation was 29 years (range, 25-38 years). The most common symptoms at presentation included headache (n=5), visual changes (n=4), hemiparesis (n=3), and seizures (n=3). The median gestational age at presentation was 20.5 weeks (range, 11-37 weeks). Of note, 8 patients (89%) delivered healthy newborns, and 1 patient terminated her pregnancy. In addition, 5 patients (56%) required neurosurgical procedures during pregnancy (gestational ages, 14-37 weeks) because of disease progression (n=2) or neurologic instability (n=3). There was 1 episode of postneurosurgery morbidity (pulmonary embolism [PE]) and no surgical maternal mortality. The median length of follow-up was 15 months (range, 6-45 months). In cases demonstrating unstable or progressive neurosurgical status past the point of fetal viability, neurosurgical intervention should be considered. The physiological and pharmacodynamic changes of pregnancy substantially affect anesthetic management. Pregnancy termination should be discussed and offered to the patient when aggressive disease necessitates immediate treatment and the fetal gestational age remains previable, although neurologically stable patients may be able to continue the pregnancy to term. Ultimately, pregnant patients with brain tumors require an individualized approach to their care under the guidance of a multidisciplinary team.

Improved survival and disease control following pembrolizumab-induced immune-related adverse events in high PD-L1 expressing non-small cell lung cancer with brain metastases.

INTRODUCTION: Immune checkpoint inhibitors have become standard of care for many patients with non-small cell lung cancer (NSCLC). These agents often cause immune-related adverse events (IRAEs), which have been associated with increased overall survival (OS). Intracranial disease control and OS for patients experiencing IRAEs with metastatic NSCLC and brain metastases have not yet been described. METHODS: We performed a single-institution, retrospective review of patients with NSCLC and existing diagnosis of brain metastasis, who underwent pembrolizumab treatment and developed any grade IRAE. The primary outcome of the study was intracranial time to treatment failure (TTF), defined from time of pembrolizumab initiation to new intracranial disease progression or death. Kaplan-Meier and Cox proportional hazard analyses were performed. RESULTS: A total of 63 patients with NSCLC brain metastasis were identified, and 24 developed IRAEs. Patients with any grade IRAEs had longer OS (21 vs. 10 months, p = 0.004), systemic TTF (15 vs. 4 months, p < 0.001) and intracranial TTF (14 vs. 5 months, p = 0.001), relative to patients without IRAEs. Presence of IRAEs and high PD-L1 (≥ 50%), but not absent/moderate PD-L1 (0-49%), had a positive association for OS, systemic TTF, and intracranial TTF. Following multivariable analysis, IRAE experienced on pembrolizumab was an independent predictor of OS, systemic TTF, and intracranial TTF. CONCLUSIONS: In our series of patients with NSCLC and brain metastases treated with pembrolizumab, IRAE presence was associated with a significant increase in OS, systemic TTF, and intracranial TTF. Future studies with increased cohorts will clarify how IRAEs should be interpreted among molecular subtypes.

Leptomeningeal Carcinomatosis: Molecular Landscape, Current Management, and Emerging Therapies.

Leptomeningeal carcinomatosis is a devastating consequence of late-stage cancer, and despite multimodal treatment, remains rapidly fatal. Definitive diagnosis requires identification of malignant cells in the cerebrospinal fluid (CSF), or frank disease on MRI. Therapy is generally palliative and consists primarily of radiotherapy and/or chemotherapy, which is administered intrathecally or systemically. Immunotherapies and novel experimental therapies have emerged as promising options for decreasing patient morbidity and mortality. In this review, the authors discuss a refined view of the molecular pathophysiology of leptomeningeal carcinomatosis, current approaches to disease management, and emerging therapies.

Intracranial Tumor Control After Immune-Related Adverse Events and Discontinuation of Immunotherapy for Melanoma.

OBJECTIVE: Immunotherapy for patients with melanoma with brain metastasis has significantly improved outcomes; however, it has also been characterized by potentially dangerous immune-related adverse events (IRAEs). Several reports have suggested that these reactions can precede improved treatment responses. For intracranial disease control, we sought to identify if such an association exists. METHODS: We conducted a retrospective chart review of patients with melanoma who underwent immunotherapy treatment after diagnosis of brain metastasis. The study cohort was then stratified into 2 groups based on their history of developing an IRAE that prompted discontinuation of that regimen. The primary outcome variable included intracranial progression-free survival (PFS). Kaplan-Meier and Cox proportional hazard analyses were used to evaluate survival and predictors of outcomes. RESULTS: Fifty-two patients met the inclusion criteria, 17 of whom experienced severe IRAEs that led to discontinuation of immunotherapy. Median intracranial PFS was 19.9 versus 10.5 months (P = 0.053) in patients who did and did not experience severe IRAEs prompting discontinuation, respectively. No additional outcome benefits were identified for systemic PFS or overall survival (mean, 33.1 months and 27.6 months, respectively). Multivariable analysis identified BRAF mutation status as a negative prognosticator of brain progression (P = 0.013; hazard ratio, 3.90). Initial treatment with BRAF inhibitor was also a negative predictor of all-cause mortality (P = 0.015; hazard ratio, 10.73). CONCLUSIONS: Immune-related adverse events may signify an underlying immunogenic response that has intracranial disease control benefits. Despite their associated side effects, immunotherapies continue to show promising outcomes as a first-line agent for melanoma with brain metastasis.

Racial and socioeconomic correlates of treatment and survival among patients with meningioma: a population-based study.

BACKGROUND: Though meningioma is the most common primary brain tumor, there is a paucity of epidemiologic studies investigating disparities in treatment and patient outcomes. Therefore, we sought to explore how sociodemographic factors are associated with rates of gross total resection (GTR) and radiotherapy as well as survival. METHODS: The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database was queried to identify adult patients with meningioma diagnosed between 2005 and 2015. Socioeconomic status (SES) was determined using a validated composite index in which patients were stratified into tertiles and quintiles. Multivariable logistic regression and Cox proportional hazards analyses were used to identify predictors of treatment and survival, respectively. RESULTS: 71,098 patients met our inclusion criteria. Low SES quintile was associated with reduced odds of receiving GTR (OR 0.76, 95% CI 0.69-0.83, p < 0.0001) and radiotherapy (OR 0.83, 95% CI 0.76-0.91, p < 0.0001) as well as worse survival (HR 1.48, 95% CI 1.41-1.56) as compared to the highest SES quintile. Black patients had reduced odds of GTR (OR 0.74, 95% CI 0.67-0.71, p < 0.0001) and worse survival (HR 1.23, 95% CI 1.18-1.29, p < 0.0001) as compared to white patients. CONCLUSIONS: This national study of patients with meningioma found socioeconomic status and race to be independent inverse correlates of likelihood of GTR, radiotherapy, and survival. Limited access to care may underlie these disparities in part, and future studies are warranted to identify specific causes for these findings.