Dose-Dependent Effects of Statins for Patients with Aneurysmal Subarachnoid Hemorrhage: Meta-Regression Analysis

© 2018 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (May 2018) in accordance with the publisher’s archiving policyObjective The study uses meta-regression analysis to quantify the dose-dependent effects of statin pharmacotherapy on vasospasm, delayed ischemic neurologic deficits (DIND), and mortality in aneurysmal subarachnoid hemorrhage. Methods Prospective, retrospective observational studies, and randomized controlled trials (RCTs) were retrieved by a systematic database search. Summary estimates were expressed as absolute risk (AR) for a given statin dose or control (placebo). Meta-regression using inverse variance weighting and robust variance estimation was performed to assess the effect of statin dose on transformed AR in a random effects model. Dose-dependence of predicted AR with 95% confidence interval (CI) was recovered by using Miller's Freeman–Tukey inverse. Results The database search and study selection criteria yielded 18 studies (2594 patients) for analysis. These included 12 RCTs, 4 retrospective observational studies, and 2 prospective observational studies. Twelve studies investigated simvastatin, whereas the remaining studies investigated atorvastatin, pravastatin, or pitavastatin, with simvastatin-equivalent doses ranging from 20 to 80 mg. Meta-regression revealed dose-dependent reductions in Freeman–Tukey-transformed AR of vasospasm (slope coefficient −0.00404, 95% CI −0.00720 to −0.00087; P = 0.0321), DIND (slope coefficient −0.00316, 95% CI −0.00586 to −0.00047; P = 0.0392), and mortality (slope coefficient −0.00345, 95% CI −0.00623 to −0.00067; P = 0.0352). Conclusions The present meta-regression provides weak evidence for dose-dependent reductions in vasospasm, DIND and mortality associated with acute statin use after aneurysmal subarachnoid hemorrhage. However, the analysis was limited by substantial heterogeneity among individual studies. Greater dosing strategies are a potential consideration for future RCT

Can We Geographically Validate a Natural Language Processing Algorithm for Automated Detection of Incidental Durotomy Across Three Independent Cohorts From Two Continents?

Background Incidental durotomy is an intraoperative complication in spine surgery that can lead to postoperative complications, increased length of stay, and higher healthcare costs. Natural language processing (NLP) is an artificial intelligence method that assists in understanding free-text notes that may be useful in the automated surveillance of adverse events in orthopaedic surgery. A previously developed NLP algorithm is highly accurate in the detection of incidental durotomy on internal validation and external validation in an independent cohort from the same country. External validation in a cohort with linguistic differences is required to assess the transportability of the developed algorithm, referred to geographical validation. Ideally, the performance of a prediction model, the NLP algorithm, is constant across geographic regions to ensure reproducibility and model validity. Question/purpose Can we geographically validate an NLP algorithm for the automated detection of incidental durotomy across three independent cohorts from two continents? Methods Patients 18 years or older undergoing a primary procedure of (thoraco)lumbar spine surgery were included. In Massachusetts, between January 2000 and June 2018, 1000 patients were included from two academic and three community medical centers. In Maryland, between July 2016 and November 2018, 1279 patients were included from one academic center, and in Australia, between January 2010 and December 2019, 944 patients were included from one academic center. The authors retrospectively studied the free-text operative notes of included patients for the primary outcome that was defined as intraoperative durotomy. Incidental durotomy occurred in 9% (93 of 1000), 8% (108 of 1279), and 6% (58 of 944) of the patients, respectively, in the Massachusetts, Maryland, and Australia cohorts. No missing reports were observed. Three datasets (Massachusetts, Australian, and combined Massachusetts and Australian) were divided into training and holdout test sets in an 80:20 ratio. An extreme gradient boosting (an efficient and flexible tree-based algorithm) NLP algorithm was individually trained on each training set, and the performance of the three NLP algorithms (respectively American, Australian, and combined) was assessed by discrimination via area under the receiver operating characteristic curves (AUC-ROC; this measures the model's ability to distinguish patients who obtained the outcomes from those who did not), calibration metrics (which plot the predicted and the observed probabilities) and Brier score (a composite of discrimination and calibration). In addition, the sensitivity (true positives, recall), specificity (true negatives), positive predictive value (also known as precision), negative predictive value, Fl-score (composite of precision and recall), positive likelihood ratio, and negative likelihood ratio were calculated. Results The combined NLP algorithm (the combined Massachusetts and Australian data) achieved excellent performance on independent testing data from Australia (AUC-ROC 0.97 [95% confidence interval 0.87 to 0.99]), Massachusetts (AUC-ROC 0.99 [95% CI 0.80 to 0.99]) and Maryland (AUC-ROC 0.95 [95% CI 0.93 to 0.97]). The NLP developed based on the Massachusetts cohort had excellent performance in the Maryland cohort (AUC-ROC 0.97 [95% CI 0.95 to 0.99]) but worse performance in the Australian cohort (AUC-ROC 0.74 [95% CI 0.70 to 0.77]). Conclusion We demonstrated the clinical utility and reproducibility of an NLP algorithm with combined datasets retaining excellent performance in individual countries relative to algorithms developed in the same country alone for detection of incidental durotomy. Further multi-institutional, international collaborations can facilitate the creation of universal NLP algorithms that improve the quality and safety of orthopaedic surgery globally. The combined NLP algorithm has been incorporated into a freely accessible web application that can be found at https://sorg-apps.shinyapps.io/nlp_incidental_durotomy/. Clinicians and researchers can use the tool to help incorporate the model in evaluating spine registries or quality and safety departments to automate detection of incidental durotomy and optimize prevention efforts

Rate of resolution of histologically verified intracranial tuberculomas

Objective: The goal of this study was to determine the rate of radiological resolution of histopathologically proven tuberculomas treated with antituberculous therapy (ATT). The effects of the size of the tuberculomas, the number of tuberculomas, and the addition of corticosteroid therapy on the rate of resolution of the tuberculomas were also studied. Methods: Twenty-eight patients (age range, 5-48 yr; 14 male and 14 female patients) with histologically proven intracranial tuberculomas were prospectively monitored with contrast-enhanced computed tomographic scans. The patients received ATT consisting of rifampicin and isoniazid for a period of 18 months, with ethambutol and/or pyrazinamide for a minimum of 3 months. Fifteen patients also received corticosteroid therapy for 1 to 6 weeks. Of the 28 patients, 17 patients underwent partial excision, 6 underwent open biopsy, and 5 underwent stereotactic biopsy of their tuberculomas. Results: Kaplan-Meier analysis revealed that, after 9 months of ATT, only 18.2% of the patients demonstrated complete resolution of their tuberculomas; even after 18 months of ATT, 69.2% of the patients had residual lesions. By 24 months, 54% of the patients demonstrated complete resolution of their tuberculomas. Although the number of tuberculomas, corticosteroid administration, prior treatment with ATT, and the duration of symptoms before presentation (<6 mo versus >6 mo) did not influence the rate of resolution, larger tuberculomas (maximal size, >4 cm) were observed to resolve more slowly than smaller tuberculomas (<4 cm) (P = 0.02). Conclusion: More than two-thirds of patients with partially excised or biopsied intracranial tuberculomas exhibited persistent lesions on computed tomographic scans, even after 18 months of ATT. Therefore, the duration of ATT for patients with intracranial tuberculomas should be based on the radiological responses of the tuberculomas. Our data suggest that some patients with intracranial tuberculomas might require prolonged periods of ATT

Targeting the Sphingolipid System as a Therapeutic Direction for Glioblastoma

Glioblastoma (GBM) is the most commonly diagnosed malignant brain tumor in adults. The prognosis for patients with GBM remains poor and largely unchanged over the last 30 years, due to the limitations of existing therapies. Thus, new therapeutic approaches are desperately required. Sphingolipids are highly enriched in the brain, forming the structural components of cell membranes, and are major lipid constituents of the myelin sheaths of nerve axons, as well as playing critical roles in cell signaling. Indeed, a number of sphingolipids elicit a variety of cellular responses involved in the development and progression of GBM. Here, we discuss the role of sphingolipids in the pathobiology of GBM, and how targeting sphingolipid metabolism has emerged as a promising approach for the treatment of GBM

Trigonal cavernous angiomas: report of three cases and review of literature

Background: Intraventricular cavernous angiomas are very rare. Only few cases of trigonal angiomas have been reported. Case Description: We report three cases of trigonal cavernous angiomas who presented with raised intracranial pressure or seizures and who underwent total excision with a good recovery. We also review the literature and discuss surgical approaches. Conclusion: On magnetic resonance imaging, intraventricular cavernous angiomas lack the hemosiderin ring characteristically seen around parenchymal cavernous angiomas. This explains why trigonal cavernous angiomas can mimic malignant neoplasm on imaging, and they should be considered in the differential diagnosis of intraventricular masses. Total excision should be the goal of surgery

SRRM4 Expands the Repertoire of Circular RNAs by Regulating Microexon Inclusion

High-throughput RNA sequencing (RNA-seq) and dedicated bioinformatics pipelines have synergized to identify an expansive repertoire of unique circular RNAs (circRNAs), exceeding 100,000 variants. While the vast majority of these circRNAs comprise canonical exonic and intronic sequences, microexons (MEs)—which occur in 30% of functional mRNA transcripts—have been entirely overlooked. CircRNAs which contain these known MEs (ME-circRNAs) could be identified with commonly utilized circRNA prediction pipelines, CIRCexplorer2 and CIRI2, but were not previously recognized as ME-circRNAs. In addition, when employing a bespoke bioinformatics pipeline for identifying RNA chimeras, called Hyb, we could also identify over 2000 ME-circRNAs which contain novel MEs at their backsplice junctions, that are uncalled by either CIRCexplorer2 or CIRI2. Analysis of circRNA-seq datasets from gliomas of varying clinical grades compared with matched control tissue has shown circRNAs have potential as prognostic markers for stratifying tumor from healthy tissue. Furthermore, the abundance of microexon-containing circRNAs (ME-circRNAs) between tumor and normal tissues is correlated with the expression of a splicing associated factor, Serine/arginine repetitive matrix 4 (SRRM4). Overexpressing SRRM4, known for regulating ME inclusion in mRNAs critical for neural differentiation, in human HEK293 cells resulted in the biogenesis of over 2000 novel ME-circRNAs, including ME-circEIF4G3, and changes in the abundance of many canonical circRNAs, including circSETDB2 and circLRBA. This shows SRRM4, in which its expression is correlated with poor prognosis in gliomas, acts as a bona fide circRNA biogenesis factor. Given the known roles of MEs and circRNAs in oncogenesis, the identification of these previously unrecognized ME-circRNAs further increases the complexity and functional purview of this non-coding RNA family

A drug screening pipeline using 2D and 3D patient-derived in vitro models for pre-clinical analysis of therapy response in glioblastoma

Glioblastoma is one of the most common and lethal types of primary brain tumor. Despite aggressive treatment with chemotherapy and radiotherapy, tumor recurrence within 6–9 months is common. To overcome this, more effective therapies targeting cancer cell stemness, invasion, metabolism, cell death resistance and the interactions of tumor cells with their surrounding microen-vironment are required. In this study, we performed a systematic review of the molecular mechanisms that drive glioblastoma progression, which led to the identification of 65 drugs/inhibitors that we screened for their efficacy to kill patient-derived glioma stem cells in two dimensional (2D) cul-tures and patient-derived three dimensional (3D) glioblastoma explant organoids (GBOs). From the screening, we found a group of drugs that presented different selectivity on different patient-derived in vitro models. Moreover, we found that Costunolide, a TERT inhibitor, was effective in reducing the cell viability in vitro of both primary tumor models as well as tumor models pre-treated with chemotherapy and radiotherapy. These results present a novel workflow for screening a relatively large groups of drugs, whose results could lead to the identification of more personalized and effective treatment for recurrent glioblastoma.</p

Endothelial, pericyte and tumor cell expression in glioblastoma identifies fibroblast activation protein (FAP) as an excellent target for immunotherapy

Objectives: Targeted immunotherapies such as chimeric antigen receptor (CAR)-T cells are emerging as attractive treatment options for glioblastoma, but rely on identification of a suitable tumor antigen. We validated a new target antigen for glioblastoma, fibroblast activation protein (FAP), by undertaking a detailed expression study of human samples. Methods: Glioblastoma and normal tissues were assessed using immunostaining, supported by analyses of published transcriptomic datasets. Short-term cultures of glioma neural stem (GNS) cells were compared to cultures of healthy astrocytes and neurons using flow cytometry. Glioblastoma tissues were dissociated and analysed by high-parameter flow cytometry and single-cell transcriptomics (scRNAseq). Results: Compared to normal brain, FAP was overexpressed at the gene and protein level in a large percentage of glioblastoma tissues, with highest levels of expression associated with poorer prognosis. FAP was also overexpressed in several paediatric brain cancers. FAP was commonly expressed by cultured GNS cells but absent from normal neurons and astrocytes. Within glioblastoma tissues, the strongest expression of FAP was around blood vessels. In fact, almost every tumor vessel was highlighted by FAP expression, whereas normal tissue vessels and cultured endothelial cells (ECs) lacked expression. Single-cell analyses of dissociated tumors facilitated a detailed characterisation of the main cellular components of the glioblastoma microenvironment and revealed that vessel-localised FAP is because of expression on both ECs and pericytes. Conclusion: Fibroblast activation protein is expressed by multiple cell types within glioblastoma, highlighting it as an ideal immunotherapy antigen to target destruction of both tumor cells and their supporting vascular network.</p