Regulatory Considerations in the Approval of Rezafungin (REZZAYO) for the Treatment of Candidemia and Invasive Candidiasis in Adults

On March 22, 2023, the FDA approved rezafungin (REZZAYO) for the treatment of candidemia and invasive candidiasis in adults with limited or no alternative treatment options. Rezafungin is an echinocandin that supports weekly dosing, enabling outpatient parenteral treatment that potentially avoids the need for a central venous catheter. Approval of rezafungin was based on a single adequate and well-controlled phase 3 study designed with a Day 30 all-cause mortality primary endpoint and 20% noninferiority margin, which demonstrated that rezafungin is noninferior to the comparator echinocandin. Nonclinical studies of rezafungin in non-human primates identified a neurotoxicity safety signal; however, rezafungin's safety profile in the completed clinical studies was similar to other FDA-approved echinocandins. Here we describe the rationale for this approval and important considerations during the review process for a flexible development program intended to expedite the availability of antimicrobial therapies to treat serious infections in patients with limited treatment options.

Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans

How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.

Automated detection of immune effector cell-associated neurotoxicity syndrome via quantitative EEG

OBJECTIVE

To develop an automated, physiologic metric of immune effector cell-associated neurotoxicity syndrome among patients undergoing chimeric antigen receptor-T cell therapy.

METHODS

We conducted a retrospective observational cohort study from 2016 to 2020 at two tertiary care centers among patients receiving chimeric antigen receptor-T cell therapy with a CD19 or B-cell maturation antigen ligand. We determined the daily neurotoxicity grade for each patient during EEG monitoring via chart review and extracted clinical variables and outcomes from the electronic health records. Using quantitative EEG features, we developed a machine learning model to detect the presence and severity of neurotoxicity, known as the EEG immune effector cell-associated neurotoxicity syndrome score.

RESULTS

The EEG immune effector cell-associated neurotoxicity syndrome score significantly correlated with the grade of neurotoxicity with a median Spearman's R2 of 0.69 (95% CI of 0.59-0.77). The mean area under receiving operator curve was greater than 0.85 for each binary discrimination level. The score also showed significant correlations with maximum ferritin (R2 0.24, p = 0.008), minimum platelets (R2 -0.29, p = 0.001), and dexamethasone usage (R2 0.42, p < 0.0001). The score significantly correlated with duration of neurotoxicity (R2 0.31, p < 0.0001).

INTERPRETATION

The EEG immune effector cell-associated neurotoxicity syndrome score possesses high criterion, construct, and predictive validity, which substantiates its use as a physiologic method to detect the presence and severity of neurotoxicity among patients undergoing chimeric antigen receptor T-cell therapy.

Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans

Synchronous bursts of high frequency oscillations ('ripples') are hypothesized to contribute to binding by facilitating integration of neuronal firing across cortical locations. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each-other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during NREM sleep and waking, in temporal and Rolandic cortices, and at distances up to 16mm. Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, and were strongly modulated by ripple phase. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple. Together, these results support the hypothesis that trans-cortical co-ripples increase the integration of neuronal firing of neurons in different cortical locations, and do so in part through phase-modulation rather than unstructured activation.

Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System

BACKGROUND AND OBJECTIVES

Brain-computer interfaces (BCIs) are being developed to restore mobility, communication, and functional independence to people with paralysis. Though supported by decades of preclinical data, the safety of chronically implanted microelectrode array BCIs in humans is unknown. We report safety results from the prospective, open-label, nonrandomized BrainGate feasibility study (NCT00912041), the largest and longest-running clinical trial of an implanted BCI.

METHODS

Adults aged 18-75 years with quadriparesis from spinal cord injury, brainstem stroke, or motor neuron disease were enrolled through 7 clinical sites in the United States. Participants underwent surgical implantation of 1 or 2 microelectrode arrays in the motor cortex of the dominant cerebral hemisphere. The primary safety outcome was device-related serious adverse events (SAEs) requiring device explantation or resulting in death or permanently increased disability during the 1-year postimplant evaluation period. The secondary outcomes included the type and frequency of other adverse events and the feasibility of the BrainGate system for controlling a computer or other assistive technologies.

RESULTS

From 2004 to 2021, 14 adults enrolled in the BrainGate trial had devices surgically implanted. The average duration of device implantation was 872 days, yielding 12,203 days of safety experience. There were 68 device-related adverse events, including 6 device-related SAEs. The most common device-related adverse event was skin irritation around the percutaneous pedestal. There were no safety events that required device explantation, no unanticipated adverse device events, no intracranial infections, and no participant deaths or adverse events resulting in permanently increased disability related to the investigational device.

DISCUSSION

The BrainGate Neural Interface system has a safety record comparable with other chronically implanted medical devices. Given rapid recent advances in this technology and continued performance gains, these data suggest a favorable risk/benefit ratio in appropriately selected individuals to support ongoing research and development.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT00912041.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that the neurosurgically placed BrainGate Neural Interface system is associated with a low rate of SAEs defined as those requiring device explantation, resulting in death, or resulting in permanently increased disability during the 1-year postimplant period.

Forecasting immune effector cell-associated neurotoxicity syndrome after chimeric antigen receptor t-cell therapy

BACKGROUND

Immune effector cell-associated neurotoxicity syndrome (ICANS) is a clinical and neuropsychiatric syndrome that can occur days to weeks following administration chimeric antigen receptor (CAR) T-cell therapy. Manifestations of ICANS range from encephalopathy and aphasia to cerebral edema and death. Because the onset and time course of ICANS is currently unpredictable, prolonged hospitalization for close monitoring following CAR T-cell infusion is a frequent standard of care.

METHODS

This study was conducted at Brigham and Women's Hospital from April 2015 to February 2020. A cohort of 199 hospitalized patients treated with CAR T-cell therapy was used to develop a combined hidden Markov model and lasso-penalized logistic regression model to forecast the course of ICANS. Model development was done using leave-one-patient-out cross validation.

RESULTS

Among the 199 patients included in the analysis 133 were male (66.8%), and the mean (SD) age was 59.5 (11.8) years. 97 patients (48.7%) developed ICANS, of which 59 (29.6%) experienced severe grades 3-4 ICANS. Median time of ICANS onset was day 9. Selected clinical predictors included maximum daily temperature, C reactive protein, IL-6, and procalcitonin. The model correctly predicted which patients developed ICANS and severe ICANS, respectively, with area under the curve of 96.7% and 93.2% when predicting 5 days ahead, and area under the curve of 93.2% and 80.6% when predicting the entire future risk trajectory looking forward from day 5. Forecasting performance was also evaluated over time horizons ranging from 1 to 7 days, using metrics of forecast bias, mean absolute deviation, and weighted average percentage error.

CONCLUSION

The forecasting model accurately predicts risk of ICANS following CAR T-cell infusion and the time course ICANS follows once it has begun.Cite Now.

Post-Acute Sequelae of SARS-CoV-2 Infection: A Descriptive Clinical Study

OBJECTIVE

The investigators aimed to describe the clinical experience of a single center reporting on neuropsychiatric findings among patients experiencing persistent symptoms as part of post-acute sequelae of SARS-CoV-2 (PASC) infection.

METHODS

Data were collected retrospectively (between February 2020 and May 2021) from a cohort (N=100) within a COVID-19 survivors study of patients with persistent symptoms enrolled after a short inpatient stay or who had been outpatients never hospitalized. Patients without confirmatory positive PCR or antibody diagnostic test results were grouped separately as presumptive cases (N=13).

RESULTS

Of the 87 patients with confirmed SARS-CoV-2, 63 (72.4%) were female, and 65 (74.7%) were White. The mean age was 49.2 years (SD=14.9). The most prevalent symptoms after COVID-19 infection were fatigue, "brain fog," headache, anxiety, and sleep issues. Attention and executive function were frequently impaired. The mean Montreal Cognitive Assessment score was 26.0 (SD=2.8). Concentration and attention as well as memory issues were both significantly correlated with the complaint of brain fog.

CONCLUSIONS

These preliminary findings suggest that post-acute sequelae of SARS-CoV-2 vary in frequency and duration with relation to premorbid history and that these conditions affect functional domains and patients' ability to return to work. Longitudinal research with larger cohorts is needed to characterize PASC and to optimize care, especially for vulnerable populations.

Propensity Scores in the Design of Observational Studies for Causal Effects

The design of any study, whether experimental or observational, that is intended to estimate the causal effects of a treatment condition relative to a control condition, refers to those activities that precede any examination of outcome variables. As defined in our 1983 article (Rosenbaum & Rubin, 1983), the propensity score is the unit-level conditional probability of assignment to treatment versus control given the observed covariates; so, the propensity score explicitly does not involve any outcome variables, in contrast to other summaries of variables sometimes used in observational studies. Balancing the distributions of covariates in the treatment and control groups by matching or balancing on the propensity score is therefore an aspect of the design of the observational study. In this invited comment on our 1983 article, we review the situation in the early 1980’s, and we recall some apparent paradoxes that propensity scores helped to resolve. We demonstrate that it is possible to balance an enormous number of low-dimensional summaries of a high-dimensional covariate, even though it is generally impossible to match individuals closely for all of the components of a high-dimensional covariate. In a sense, there is only one crucial observed covariate, the propensity score, and there is one crucial unobserved covariate, the ‘principal unobserved covariate’. The propensity score and the principal unobserved covariate are equal when treatment assignment is strongly ignorable, that is, unconfounded. Controlling for observed covariates is a prelude to the crucial step from association to causation, the step that addresses potential biases from unmeasured covariates. The design of an observational study also prepares for the step to causation: by selecting comparisons to increase the design sensitivity, by seeking opportunities to detect bias, by seeking mutually supportive evidence affected by different biases, by incorporating quasi-experimental devices such as multiple control groups, and by including the economist’s instruments. All of these considerations reflect the formal development of sensitivity analyses that were largely informal prior to the 1980s.

Learned Motor Patterns Are Replayed in Human Motor Cortex during Sleep

Consolidation of memory is believed to involve offline replay of neural activity. While amply demonstrated in rodents, evidence for replay in humans, particularly regarding motor memory, is less compelling. To determine whether replay occurs after motor learning, we sought to record from motor cortex during a novel motor task and subsequent overnight sleep. A 36-year-old man with tetraplegia secondary to cervical spinal cord injury enrolled in the ongoing BrainGate brain-computer interface pilot clinical trial had two 96-channel intracortical microelectrode arrays placed chronically into left precentral gyrus. Single- and multi-unit activity was recorded while he played a color/sound sequence matching memory game. Intended movements were decoded from motor cortical neuronal activity by a real-time steady-state Kalman filter that allowed the participant to control a neurally driven cursor on the screen. Intracortical neural activity from precentral gyrus and 2-lead scalp EEG were recorded overnight as he slept. When decoded using the same steady-state Kalman filter parameters, intracortical neural signals recorded overnight replayed the target sequence from the memory game at intervals throughout at a frequency significantly greater than expected by chance. Replay events occurred at speeds ranging from 1 to 4 times as fast as initial task execution and were most frequently observed during slow-wave sleep. These results demonstrate that recent visuomotor skill acquisition in humans may be accompanied by replay of the corresponding motor cortex neural activity during sleep.SIGNIFICANCE STATEMENT Within cortex, the acquisition of information is often followed by the offline recapitulation of specific sequences of neural firing. Replay of recent activity is enriched during sleep and may support the consolidation of learning and memory. Using an intracortical brain-computer interface, we recorded and decoded activity from motor cortex as a human research participant performed a novel motor task. By decoding neural activity throughout subsequent sleep, we find that neural sequences underlying the recently practiced motor task are repeated throughout the night, providing direct evidence of replay in human motor cortex during sleep. This approach, using an optimized brain-computer interface decoder to characterize neural activity during sleep, provides a framework for future studies exploring replay, learning, and memory.

Antiseizure Medication Treatment and Outcomes in Patients with Subarachnoid Hemorrhage Undergoing Continuous EEG Monitoring

BACKGROUND

Patients with aneurysmal subarachnoid hemorrhage (aSAH) with electroencephalographic epileptiform activity (seizures, periodic and rhythmic patterns, and sporadic discharges) are frequently treated with antiseizure medications (ASMs). However, the safety and effectiveness of ASM treatment for epileptiform activity has not been established. We used observational data to investigate the effectiveness of ASM treatment in patients with aSAH undergoing continuous electroencephalography (cEEG) to develop a causal hypothesis for testing in prospective trials.

METHODS

This was a retrospective single-center cohort study of patients with aSAH admitted between 2011 and 2016. Patients underwent ≥ 24 h of cEEG within 4 days of admission. All patients received primary ASM prophylaxis until aneurysm treatment (typically within 24 h of admission). Treatment exposure was defined as reinitiation of ASMs after aneurysm treatment and cEEG initiation. We excluded patients with non-cEEG indications for ASMs (e.g., epilepsy, acute symptomatic seizures). Outcomes measures were 90-day mortality and good functional outcome (modified Rankin Scale scores 0-3). Propensity scores were used to adjust for baseline covariates and disease severity.

RESULTS

Ninety-four patients were eligible (40 continued ASM treatment; 54 received prophylaxis only). ASM continuation was not significantly associated with higher 90-day mortality (propensity-adjusted hazard ratio [HR] = 2.01 [95% confidence interval (CI) 0.57-7.02]). ASM continuation was associated with lower likelihood for 90-day good functional outcome (propensity-adjusted HR = 0.39 [95% CI 0.18-0.81]). In a secondary analysis, low-intensity treatment (low-dose single ASM) was not significantly associated with mortality (propensity-adjusted HR = 0.60 [95% CI 0.10-3.59]), although it was associated with a lower likelihood of good outcome (propensity-adjusted HR = 0.37 [95% CI 0.15-0.91]), compared with prophylaxis. High-intensity treatment (high-dose single ASM, multiple ASMs, or anesthetics) was associated with higher mortality (propensity-adjusted HR = 6.80 [95% CI 1.67-27.65]) and lower likelihood for good outcomes (propensity-adjusted HR = 0.30 [95% CI 0.10-0.94]) compared with prophylaxis only.

CONCLUSIONS

Our findings suggest the testable hypothesis that continuing ASMs in patients with aSAH with cEEG abnormalities does not improve functional outcomes. This hypothesis should be tested in prospective randomized studies.

Use of Transcranial Doppler as a Biomarker of CAR T Cell-Related Neurotoxicity

Background and Objectives

To examine the relationship between transcranial Doppler (TCD) mean flow velocity (MFV) and the severity and temporal onset of neurotoxicity after chimeric antigen receptor (CAR) T-cell therapy in patients with relapsed lymphoma.

Methods

We identified a cohort of 165 patients with relapsed or refractory B-cell lymphoma who received CAR T-cell therapy. TCDs were performed at baseline, treatment day 5, and throughout hospitalization based on development of neurologic symptoms. We assessed the percent change in velocity from baseline in each of the 6 major supratentorial arteries and the relationship of these values to development and timing of neurotoxicity.

Results

Our cohort was 30% female with an average age of 60 years. Of patients with TCDs performed, 63% developed neurotoxicity, and 32% had severe neurotoxicity. The median time of neurotoxicity onset was day 7. Higher maximum percent change in MFV across all vessels was significantly associated with likelihood of developing neurotoxicity (p = 0.0002) and associated with severe neurotoxicity (p = 0.0421). We found that with increased percent change in MFV, the strength of correlation between day of TCD velocity change and day of neurotoxicity onset increased. There was no single vessel in which increase in MFV was associated with neurotoxicity.

Discussion

Our study demonstrates an association between increase in TCD MFV and the development of neurotoxicity, as well as timing of neurotoxicity onset. We believe that TCD ultrasound may be used as a bedside functional biomarker in CAR T-cell patients and may guide immunologic interventions to manage toxicity in this complex patient group.

Neuron, control thyself!

This scientific commentary refers to ‘Volitional control of individual neurons in the human brain’ by Patel et al. (doi:10.1093/brain/awab370).

Neurologic Complications in Patients with Cancer

Neurologic symptoms are commonly seen in patients with cancer and can be among the most challenging to diagnose and manage. It is often difficult to determine if new neurologic symptoms are secondary to direct effects of a malignant lesion, systemic complications of disease, paraneoplastic disorders, or side effects of cancer treatment itself. However, early diagnosis and treatment of each of these conditions can improve patients' quality of life and long-term functional outcomes. In this review, we describe a systematic approach to the diagnosis of new neurologic symptoms in patients with known malignancy. We have categorized the neurologic complications of cancer through a mechanistic approach, with an emphasis on ascertaining underlying pathophysiology to guide treatment choice. This review focuses on the acute neurologic complications of cancer that require hospital admission.

EEG findings in CART T associated neurotoxicity: clinical and radiological correlations

BACKGROUND

While EEG is frequently reported as abnormal after CAR T cell therapy, its clinical significance remains unclear. We aim to systematically describe EEG features in a large single-center cohort and correlate them with clinical and radiological findings.

METHODS

We retrospectively identified patients undergoing CAR T cell therapy who had continuous EEG. Neurotoxicity grades, detailed neurological symptoms, and brain MRI or FDG-PET were obtained. Correlation between clinical and radiological findings and EEG features was assessed.

RESULTS

In 81 patients with median neurotoxicity grade 3 (IQR 2-3), diffuse EEG background slowing was the most common finding and correlated with neurotoxicity severity (p <0.001). A total of 42 patients had rhythmic or periodic patterns, 16 of them within the ictal-interictal-continuum (IIC), 5 with clinical seizures, and 3 with only electrographic seizures. Focal EEG abnormalities, consisting of lateralized periodic discharges (LPD, n=1), lateralized rhythmic delta activity (LRDA, n=6), or focal slowing (n=19), were found in 22 patients. All patients with LRDA, LPD, and 10/19 patients with focal slowing had focal clinical symptoms concordant with these EEG abnormalities. In addition, these focal EEG changes often correlated with PET hypometabolism or MRI hypoperfusion, in absence of a structural lesion.

CONCLUSION

In adult patients experiencing neurotoxicity after CAR T cell infusion, EEG degree of background disorganization correlated with neurotoxicity severity. IIC patterns and focal EEG abnormalities are frequent and often correlate with focal clinical symptoms and with PET-hypometabolism/MRI-hypoperfusion, without structural lesion. The etiology of these findings remains to be elucidated.

Early Brain Injury and Soluble ST2 After Nontraumatic Subarachnoid Hemorrhage

[Figure: see text].

Clinical Predictors of Neurotoxicity After Chimeric Antigen Receptor T-Cell Therapy

Importance

Chimeric antigen receptor (CAR) T-cell therapy for relapsed or refractory hematologic malignant neoplasm causes severe neurologic adverse events ranging from encephalopathy and aphasia to cerebral edema and death. The cause of neurotoxicity is incompletely understood, and its unpredictability is a reason for prolonged hospitalization after CAR T-cell infusion.

Objective

To identify clinical and laboratory parameters predictive of neurotoxicity and to develop a prognostic score associated with its risk.

Design, Setting, and Participants

This single-center diagnostic/prognostic accuracy study was conducted at Brigham and Women's Hospital/Dana Farber Cancer Institute from April 2015 to February 2020. A consecutive sample of all patients undergoing CAR T-cell therapy with axicabtagene ciloleucel for relapsed or refractory lymphoma were assessed for inclusion (n = 213). Patients who had previously received CAR T cells or who were treated for mantle cell lymphoma were excluded (n = 9). Patients were followed up for a minimum of 30 days from the date of CAR T-cell infusion.

Main Outcomes and Measures

The primary outcomes were measures of performance (accuracy, sensitivity, specificity, area under the curve) of a diagnostic tool to predict the occurrence of CAR-associated neurotoxicity, as graded by the Common Terminology Criteria for Adverse Events criteria.

Results

Two hundred four patients (127 men [62.2%]; mean [SD] age, 60.0 [12.1] years) were included in the analysis, of which 126 (61.8%) comprised a derivation cohort and 78 (38.2%), an internal validation cohort. Seventy-three patients (57.9%) in the derivation cohort and 45 patients (57.7%) in the validation cohort experienced neurotoxicity. Clinical and laboratory values obtained early in admission were used to develop a multivariable score that can predict the subsequent development of neurotoxicity; when tested on an internal validation cohort, this score had an area under the curve of 74%, an accuracy of 77%, a sensitivity of 82%, and a specificity of 70% (positive:negative likelihood ratio, 2.71:0.26).

Conclusions and Relevance

The score developed in this study may help predict which patients are likely to experience CAR T-cell-associated neurotoxicity. The score can be used for triaging and resource allocation and may allow a large proportion of patients to be discharged from the hospital early.

US Food and Drug Administration (FDA): Benefit-Risk Considerations for Cefiderocol (Fetroja®)

In November 2019, the Food and Drug Administration (FDA) approved cefiderocol for the treatment of complicated urinary tract infections (cUTI) including pyelonephritis caused by susceptible gram-negative bacteria in adults with limited to no alternative treatment options based on a randomized, double-blind, noninferiority cUTI trial (APEKS-cUTI). In a randomized, open-label trial (CREDIBLE-CR) in patients with cUTI, nosocomial pneumonia, bloodstream infections, or sepsis due to carbapenem-resistant gram-negative bacteria, an increase in all-cause mortality was observed in patients treated with cefiderocol as compared to best available therapy. The cause of the increased mortality was not established, but some deaths were attributed to treatment failure. Preliminary data from a randomized, double-blind trial (APEKS-NP) in patients with nosocomial pneumonia due to carbapenem-susceptible gram-negative bacteria showed a similar rate of mortality as compared to meropenem. We describe the uncertainties and challenges in the interpretation of the CREDIBLE-CR trial and some benefit-risk considerations for the use of cefiderocol in clinical practice. Clinical Trials Registration: NCT02321800.

The importance of having a conceptual stage when reporting non-randomized studies

Formal guidelines for statistical reporting of non-randomized studies are important for journals that publish results of such studies. Although it is gratifying to see some journals providing guidelines for statistical reporting, we feel that the current guidelines that we have seen are not entirely adequate when the study is used to draw causal conclusions. We therefore offer some comments on ways to improve these studies. In particular, we discuss and illustrate what we regard as the need for an essential initial stage of any such statistical analysis, the conceptual stage, which formally describes the embedding of a non-randomized study within a hypothetical randomized experiment.

Neurological complications of cancer immunotherapy (CAR T cells)

Chimeric antigen receptor (CAR) T cell therapy has become an indispensable tool in the treatment of advanced malignancy, however, it is associated with significant neurologic toxicity. The pathophysiology of CAR T-cell associated neurotoxicity is incompletely understood, and the specific risk factors have only recently begun to be characterized. Despite a growing clinical experience with CAR T cell therapy, the unpredictability of neurologic symptoms remains a source of great anxiety for patients and practitioners alike, and a major limitation for more widespread adoption of this important treatment modality. The purpose of this review is to familiarize clinicians with the typical clinical manifestations and salient features of CAR T cell associated neurotoxicity. We place an emphasis on highlighting the clinical and laboratory markers that may be helpful for predicting clinical course, allowing teams to anticipate necessary supportive measures. We will also review the appropriate diagnostic workup for CAR T cell neurotoxicity and current treatment recommendations.

Anatomically Coiled Internal Carotid Artery Resulting in Severe Dysphagia and Burning Mouth Syndrome

This is a report of a 65-year-old female presenting with symptoms of dysphagia due to a coiled left internal carotid artery, treated with resection and primary repair. Dysphagia lusoria is more commonly caused by aortic arch anomalies, aberrant subclavian or common carotid arteries. Internal carotid tortuosity as a cause of severe dysphagia and burning mouth syndrome is highly unusual. A literature review examines the etiology, natural history, and treatment options.

Heterogeneous ozone effects on the DNA methylome of bronchial cells observed in a crossover study

We used a randomized crossover experiment to estimate the effects of ozone (vs. clean air) exposure on genome-wide DNA methylation of target bronchial epithelial cells, using 17 volunteers, each randomly exposed on two separated occasions to clean air or 0.3-ppm ozone for two hours. Twenty-four hours after exposure, participants underwent bronchoscopy to collect epithelial cells whose DNA methylation was measured using the Illumina 450 K platform. We performed global and regional tests examining the ozone versus clean air effect on the DNA methylome and calculated Fisher-exact p-values for a series of univariate tests. We found little evidence of an overall effect of ozone on the DNA methylome but some suggestive changes in PLSCR1, HCAR1, and LINC00336 DNA methylation after ozone exposure relative to clean air. We observed some participant-to-participant heterogeneity in ozone responses.

Electrographic predictors of successful weaning from anaesthetics in refractory status epilepticus

Intravenous third-line anaesthetic agents are typically titrated in refractory status epilepticus to achieve either seizure suppression or burst suppression on continuous EEG. However, the optimum treatment paradigm is unknown and little data exist to guide the withdrawal of anaesthetics in refractory status epilepticus. Premature withdrawal of anaesthetics risks the recurrence of seizures, whereas the prolonged use of anaesthetics increases the risk of treatment-associated adverse effects. This study sought to measure the accuracy of features of EEG activity during anaesthetic weaning in refractory status epilepticus as predictors of successful weaning from intravenous anaesthetics. We prespecified a successful anaesthetic wean as the discontinuation of intravenous anaesthesia without developing recurrent status epilepticus, and a wean failure as either recurrent status epilepticus or the resumption of anaesthesia for the purpose of treating an EEG pattern concerning for incipient status epilepticus. We evaluated two types of features as predictors of successful weaning: spectral components of the EEG signal, and spatial-correlation-based measures of functional connectivity. The results of these analyses were used to train a classifier to predict wean outcome. Forty-seven consecutive anaesthetic weans (23 successes, 24 failures) were identified from a single-centre cohort of patients admitted with refractory status epilepticus from 2016 to 2019. Spectral components of the EEG revealed no significant differences between successful and unsuccessful weans. Analysis of functional connectivity measures revealed that successful anaesthetic weans were characterized by the emergence of larger, more densely connected, and more highly clustered spatial functional networks, yielding 75.5% (95% confidence interval: 73.1-77.8%) testing accuracy in a bootstrap analysis using a hold-out sample of 20% of data for testing and 74.6% (95% confidence interval 73.2-75.9%) testing accuracy in a secondary external validation cohort, with an area under the curve of 83.3%. Distinct signatures in the spatial networks of functional connectivity emerge during successful anaesthetic liberation in status epilepticus; these findings are absent in patients with anaesthetic wean failure. Identifying features that emerge during successful anaesthetic weaning may allow faster and more successful anaesthetic liberation after refractory status epilepticus.

The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability

Correlated variability in cortical activity is ubiquitously quenched following stimulus onset, in a stimulus-dependent manner. These modulations have been attributed to circuit dynamics involving either multiple stable states (“attractors”) or chaotic activity. Here we show that a qualitatively different dynamical regime, involving fluctuations about a single, stimulus-driven attractor in a loosely balanced excitatory-inhibitory network (the stochastic “stabilized supralinear network”), best explains these modulations. Given the supralinear input/output functions of cortical neurons, increased stimulus drive strengthens effective network connectivity. This shifts the balance from interactions that amplify variability to suppressive inhibitory feedback, quenching correlated variability around more strongly driven steady states. Comparing to previously published and original data analyses, we show that this mechanism, unlike previous proposals, uniquely accounts for the spatial patterns and fast temporal dynamics of variability suppression. Specifying the cortical operating regime is key to understanding the computations underlying perception.

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A simple network model explains stimulus-tuning of cortical variability suppression

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Inhibition stabilizes recurrently interacting neurons with supralinear I/O functions

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Stimuli strengthen inhibitory stabilization around a stable state, quenching variability

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Single-trial V1 data are compatible with this model and rules out competing proposals

Inflammation and Demyelination

Autoimmune disease affecting the central nervous system is a common cause for admission to the neurointensive care unit. Although well-described clinical syndromes exist, patients more commonly present with progressive neurologic dysfunction and some combination of laboratory and radiographic evidence of central nervous system inflammation. The urgency to intervene to prevent permanent damage to the nervous system often conflicts with diagnostic uncertainty. This chapter outlines some of the basic diagnostic and therapeutic principles of autoimmune diseases of the central nervous system. The chapter characterizes disorders not as a list of individual disease entities but rather as clusters of syndromes based on common underlying mechanisms of immune dysfunction. This approach focuses on early interventions rather than precise diagnosis. As our understanding of the immune system continues to grow, this framework will allow for a more sophisticated approach to the management of patients with these complex, often devastating but frequently reversible, neurologic illnesses.

Analysis Populations in Anti-Infective Clinical Trials: Whom to Analyze?

Investigators can choose to analyze different patient populations in clinical trials. The different analysis populations answer different types of research questions, estimate different quantities, and evaluate the robustness of the trial results. Various analysis populations have different strengths and weaknesses depending on the type of question being addressed and the potential for bias from the selection of various groups of trial participants. We discuss analysis populations in the context of anti-infective clinical trials.

Autoimmune Encephalitis in Critical Care: Optimizing Immunosuppression

Autoimmune diseases affecting the nervous systems are a common cause of admission to the intensive care unit (ICU). Although there exist several well-described clinical syndromes, patients more commonly present with progressive neurologic dysfunction and laboratory and radiographic evidence of central nervous system (CNS) inflammation. In the critical care setting, the urgency to intervene to prevent permanent damage to the nervous system and secondary injury from the systemic manifestations of these syndromes often conflicts with diagnostic uncertainty. Furthermore, treatment is limited by current therapeutic agents that remain non-specific for individual diseases, especially for those whose pathophysiology remains unclear. Primary autoimmune, paraneoplastic, parainfectious, and iatrogenic neurologic disorders all share the common underlying pathophysiology of an adaptive immune response directed against an antigen within the nervous system. Several different mechanisms of immune dysfunction are responsible for pathogenesis within each of these categories of disease, and it is at this level of pathophysiology that the most effective and appropriate therapeutic decisions are made. In this review, we outline the basic diagnostic and therapeutic principles in the management of autoimmune diseases of the nervous system in the ICU. We approach these disorders not as lists of distinct clinical syndromes or molecular targets of autoimmunity but rather as clusters of syndromes based on these common underlying mechanisms of immune dysfunction. This approach emphasizes early intervention over precise diagnosis. As our understanding of the immune system continues to grow, this framework will allow for a more sophisticated approach to the management of patients with these complex, often devastating but frequently reversible, neurologic illnesses.

Evaluations of the Optimal Discovery Procedure for Multiple Testing

The Optimal Discovery Procedure (ODP) is a method for simultaneous hypothesis testing that attempts to gain power relative to more standard techniques by exploiting multivariate structure [1]. Specializing to the example of testing whether components of a Gaussian mean vector are zero, we compare the power of the ODP to a Bonferroni-style method and to the Benjamini-Hochberg method when the testing procedures aim to respectively control certain Type I error rate measures, such as the expected number of false positives or the false discovery rate. We show through theoretical results, numerical comparisons, and two microarray examples that when the rejection regions for the ODP test statistics are chosen such that the procedure is guaranteed to uniformly control a Type I error rate measure, the technique is generally less powerful than competing methods. We contrast and explain these results in light of previously proven optimality theory for the ODP. We also compare the ordering given by the ODP test statistics to the standard rankings based on sorting univariate p-values from smallest to largest. In the cases we considered the standard ordering was superior, and ODP rankings were adversely impacted by correlation.

Estimation of causal effects of binary treatments in unconfounded studies with one continuous covariate

The estimation of causal effects in nonrandomized studies should comprise two distinct phases: design, with no outcome data available; and analysis of the outcome data according to a specified protocol. Here, we review and compare point and interval estimates of common statistical procedures for estimating causal effects (i.e. matching, subclassification, weighting, and model-based adjustment) with a scalar continuous covariate and a scalar continuous outcome. We show, using an extensive simulation, that some highly advocated methods have poor operating characteristics. In many conditions, matching for the point estimate combined with within-group matching for sampling variance estimation, with or without covariance adjustment, appears to be the most efficient valid method of those evaluated. These results provide new conclusions and advice regarding the merits of currently used procedures.

Emerging Cases of Powassan Virus Encephalitis in New England: Clinical Presentation, Imaging, and Review of the Literature

BACKGROUND

Powassan virus (POWV) is a rarely diagnosed cause of encephalitis in the United States. In the Northeast, it is transmitted by Ixodes scapularis, the same vector that transmits Lyme disease. The prevalence of POWV among animal hosts and vectors has been increasing. We present 8 cases of POWV encephalitis from Massachusetts and New Hampshire in 2013-2015.

METHODS

We abstracted clinical and epidemiological information for patients with POWV encephalitis diagnosed at 2 hospitals in Massachusetts from 2013 to 2015. We compared their brain imaging with those in published findings from Powassan and other viral encephalitides.

RESULTS

The patients ranged in age from 21 to 82 years, were, for the most part, previously healthy, and presented with syndromes of fever, headache, and altered consciousness. Infections occurred from May to September and were often associated with known tick exposures. In all patients, cerebrospinal fluid analyses showed pleocytosis with elevated protein. In 7 of 8 patients, brain magnetic resonance imaging demonstrated deep foci of increased T2/fluid-attenuation inversion recovery signal intensity.

CONCLUSIONS

We describe 8 cases of POWV encephalitis in Massachusetts and New Hampshire in 2013-2015. Prior to this, there had been only 2 cases of POWV encephalitis identified in Massachusetts. These cases may represent emergence of this virus in a region where its vector, I. scapularis, is known to be prevalent or may represent the emerging diagnosis of an underappreciated pathogen. We recommend testing for POWV in patients who present with encephalitis in the spring to fall in New England.

Tax-exempt hospitals and community benefit: new directions in policy and practice

The current community benefit standard for nonprofit hospital tax exemption has been the subject of mounting criticism. Many different constituencies have advanced the view that in its present form it fails to ensure that nonprofit hospitals provide adequate benefits to their communities in exchange for their tax exemption. In contrast, hospitals have often expressed the concern that the community benefit standard in its current form is vague and therefore difficult to comply with. Various suggestions have been made regarding how the existing community benefit standard could be improved or even replaced. In this article, we first discuss the historical and legal development of the community benefit standard. We then present the key controversies that have emerged in recent years and the policy responses attempted thus far. Finally, we evaluate possible future policy directions, which reform efforts could follow.

The stabilized supralinear network: a unifying circuit motif underlying multi-input integration in sensory cortex

Neurons in sensory cortex integrate multiple influences to parse objects and support perception. Across multiple cortical areas, integration is characterized by two neuronal response properties: (1) surround suppression--modulatory contextual stimuli suppress responses to driving stimuli; and (2) "normalization"--responses to multiple driving stimuli add sublinearly. These depend on input strength: for weak driving stimuli, contextual influences facilitate or more weakly suppress and summation becomes linear or supralinear. Understanding the circuit operations underlying integration is critical to understanding cortical function and disease. We present a simple, general theory. A wealth of integrative properties, including the above, emerge robustly from four cortical circuit properties: (1) supralinear neuronal input/output functions; (2) sufficiently strong recurrent excitation; (3) feedback inhibition; and (4) simple spatial properties of intracortical connections. Integrative properties emerge dynamically as circuit properties, with excitatory and inhibitory neurons showing similar behaviors. In new recordings in visual cortex, we confirm key model predictions.

Analysis of the stabilized supralinear network

We study a rate-model neural network composed of excitatory and inhibitory neurons in which neuronal input-output functions are power laws with a power greater than 1, as observed in primary visual cortex. This supralinear input-output function leads to supralinear summation of network responses to multiple inputs for weak inputs. We show that for stronger inputs, which would drive the excitatory subnetwork to instability, the network will dynamically stabilize provided feedback inhibition is sufficiently strong. For a wide range of network and stimulus parameters, this dynamic stabilization yields a transition from supralinear to sublinear summation of network responses to multiple inputs. We compare this to the dynamic stabilization in the balanced network, which yields only linear behavior. We more exhaustively analyze the two-dimensional case of one excitatory and one inhibitory population. We show that in this case, dynamic stabilization will occur whenever the determinant of the weight matrix is positive and the inhibitory time constant is sufficiently small, and analyze the conditions for supersaturation, or decrease of firing rates with increasing stimulus contrast (which represents increasing input firing rates). In work to be presented elsewhere, we have found that this transition from supralinear to sublinear summation can explain a wide variety of nonlinearities in cerebral cortical processing.

A model of electrophysiological heterogeneity in periglomerular cells

Olfactory bulb (OB) periglomerular (PG) cells are heterogeneous with respect to several features, including morphology, connectivity, patterns of protein expression, and electrophysiological properties. However, these features rarely correlate with one another, suggesting that the differentiating properties of PG cells may arise from multiple independent adaptive variables rather than representing discrete cell classes. We use computational modeling to assess this hypothesis with respect to electrophysiological properties. Specifically, we show that the heterogeneous electrophysiological properties demonstrated in PG cell recordings can be explained solely by differences in the relative expression levels of ion channel species in the cell, without recourse to modifying channel kinetic properties themselves. This PG cell model can therefore be used as the basis for diverse cellular and network-level analyses of OB computations. Moreover, this simple basis for heterogeneity contributes to an emerging hypothesis that glomerular-layer interneurons may be better described as a single population expressing distributions of partially independent, potentially plastic properties, rather than as a set of discrete cell classes.

Evaluating hospitals' provision of community benefit: an argument for an outcome-based approach to nonprofit hospital tax exemption

Nonprofit hospitals are exempt from federal income taxation if they pass organizational and operational tests, including satisfying the community-benefit standard. Policymakers, however, have questioned the adequacy of the community benefits that nonprofit hospitals provide in exchange for these exemptions. The Internal Revenue Service recently responded to these concerns by redesigning its tax forms for nonprofit hospitals. The new Form 990 Schedule H requires nonprofit hospitals to provide additional information about their community-benefit activities. This new reporting requirement, however, places an undue focus on input-based community-benefit indicators, in particular expenditures. We argue that expanding the current input-based reporting requirement to include not only monetary inputs but also population health outcomes would achieve greater benefit for society.

Robust estimation of causal effects of binary treatments in unconfounded studies with dichotomous outcomes

The estimation of causal effects has been the subject of extensive research. In unconfounded studies with a dichotomous outcome, Y, Cangul, Chretien, Gutman and Rubin (2009) demonstrated that logistic regression for a scalar continuous covariate X is generally statistically invalid for testing null treatment effects when the distributions of X in the treated and control populations differ and the logistic model for Y given X is misspecified. In addition, they showed that an approximately valid statistical test can be generally obtained by discretizing X followed by regression adjustment within each interval defined by the discretized X. This paper extends the work of Cangul et al. 2009 in three major directions. First, we consider additional estimation procedures, including a new one that is based on two independent splines and multiple imputation; second, we consider additional distributional factors; and third, we examine the performance of the procedures when the treatment effect is non-null. Of all the methods considered and in most of the experimental conditions that were examined, our proposed new methodology appears to work best in terms of point and interval estimation.

When trade law meets public health evidence: the World Trade Organization and clove cigarettes

A recent trade dispute between the USA and Indonesia, overseen by the World Trade Organization, challenges piecemeal approaches to tobacco regulation.

Statistical issues and limitations in personalized medicine research with clinical trials

We discuss using clinical trial data to construct and evaluate rules that use baseline covariates to assign different treatments to different patients. Given such a candidate personalization rule, we first note that its performance can often be evaluated without actually applying the rule to subjects, and a class of estimators is characterized from a statistical efficiency standpoint. We also point out a recently noted reduction of the rule construction problem to a classification task and extend results in this direction. Together these facts suggest a natural form of cross-validation in which a personalized medicine rule can be constructed from clinical trial data using standard classification tools and then evaluated in a replicated trial. Because replication is often required by the FDA to provide evidence of safety and efficacy before pharmaceutical drugs can be marketed, there are abundant data with which to explore the potential benefits of more tailored therapy. We constructed and evaluated personalized medicine rules using simulations based on two active-controlled randomized clinical trials of antibacterial drugs for the treatment of skin and skin structure infections. Unfortunately we present negative results that did not suggest benefit from personalization. We discuss the implications of this finding and why statistical approaches to personalized medicine problems will often face difficult challenges.

Testing treatment effects in unconfounded studies under model misspecification: logistic regression, discretization, and their combination

Logistic regression is commonly used to test for treatment effects in observational studies. If the distribution of a continuous covariate differs between treated and control populations, logistic regression yields an invalid hypothesis test even in an uncounfounded study if the link is not logistic. This flaw is not corrected by the commonly used technique of discretizing the covariate into intervals. A valid test can be obtained by discretization followed by regression adjustment within each interval.

Making all the children above average: ethical and regulatory concerns for pediatricians in pediatric enhancement research

Building on the knowledge generated by the long history of disease-oriented research, the next few decades will witness an explosion of biomedical enhancements to make people faster, stronger, smarter, less forgetful, happier, prettier, and live longer. Growing interest in pediatric enhancements is likely to stimulate the conduct of enhancement research involving children. However, guidelines for the protection of human subjects were developed for investigations of therapeutic modalities. To date, virtually no attention has been paid to whether these rules would be appropriate for investigations to establish the safety and efficacy of technologies intended for enhancement rather than therapeutic uses and, if not, whether ethically acceptable rules could be designed. This article discusses whether the current guidelines for pediatric research provide appropriate protections for pediatric subjects in enhancement research and considers what additional protections might be necessary.

Variation in the large-scale organization of gene expression levels in the hippocampus relates to stable epigenetic variability in behavior

BACKGROUND

Despite sharing the same genes, identical twins demonstrate substantial variability in behavioral traits and in their risk for disease. Epigenetic factors-DNA and chromatin modifications that affect levels of gene expression without affecting the DNA sequence-are thought to be important in establishing this variability. Epigenetically-mediated differences in the levels of gene expression that are associated with individual variability traditionally are thought to occur only in a gene-specific manner. We challenge this idea by exploring the large-scale organizational patterns of gene expression in an epigenetic model of behavioral variability.

METHODOLOGY/FINDINGS

To study the effects of epigenetic influences on behavioral variability, we examine gene expression in genetically identical mice. Using a novel approach to microarray analysis, we show that variability in the large-scale organization of gene expression levels, rather than differences in the expression levels of specific genes, is associated with individual differences in behavior. Specifically, increased activity in the open field is associated with increased variance of log-transformed measures of gene expression in the hippocampus, a brain region involved in open field activity. Early life experience that increases adult activity in the open field also similarly modifies the variance of gene expression levels. The same association of the variance of gene expression levels with behavioral variability is found with levels of gene expression in the hippocampus of genetically heterogeneous outbred populations of mice, suggesting that variation in the large-scale organization of gene expression levels may also be relevant to phenotypic differences in outbred populations such as humans. We find that the increased variance in gene expression levels is attributable to an increasing separation of several large, log-normally distributed families of gene expression levels. We also show that the presence of these multiple log-normal distributions of gene expression levels is a universal characteristic of gene expression in eurkaryotes. We use data from the MicroArray Quality Control Project (MAQC) to demonstrate that our method is robust and that it reliably detects biological differences in the large-scale organization of gene expression levels.

CONCLUSIONS

Our results contrast with the traditional belief that epigenetic effects on gene expression occur only at the level of specific genes and suggest instead that the large-scale organization of gene expression levels provides important insights into the relationship of gene expression with behavioral variability. Understanding the epigenetic, genetic, and environmental factors that regulate the large-scale organization of gene expression levels, and how changes in this large-scale organization influences brain development and behavior will be a major future challenge in the field of behavioral genomics.